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Papers

2021

  • [PDF] Budd, Matthew and Duckworth, Paul and Hawes, Nick and Lacerda, Bruno, "Mission Planning in Unknown Environments as Bayesian Reinforcement Learning", IJCAI 2021 Workshop on Robust and Reliable Autonomy in the Wild (R2AW), 2021.

  • [PDF] Costen, Clarissa and Rigter, Marc and Lacerda, Bruno and Hawes, Nick, "Mixed Observability MDPs for Shared Autonomy with Uncertain Human Behaviour", IJCAI 2021 Workshop on Robust and Reliable Autonomy in the Wild (R2AW), 2021.

  • [PDF] Rutherford, Alex and Duckworth, Paul and Hawes, Nick and Lacerda, Bruno, "Motion Planning in Uncertain Environments with Rapidly-Exploring Random Markov Decision Processes", Proceedings of the 2021 European Conference on Mobile Robots (ECMR), 2021.

  • [PDF] Paarth Shah, Avadesh Meduri, Wolfgang Xaver Merkt, Majid Khadiv, Ioannis Havoutis and Ludovic Righetti, "Rapid Convex Optimization of Centroidal Dynamics Using Block Coordinate Descent", IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2021.

  • [PDF] Mark Nicholas Finean, Wolfgang Xaver Merkt and Ioannis Havoutis, "Simultaneous Scene Reconstruction and Whole-Body Motion Planning for Safe Operation in Dynamic Environments", IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2021.
  • [PDF] Carlo Tiseo, Wolfgang Merkt, Keyhan Kouhkiloui Babarahmati, Wouter Wolfslag, Ioannis Havoutis, Sethu Vijayakumar and Michael Mistry, "HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems", IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, Volume 29, Pages 1432 - 1440, DOI 10.1109/TNSRE.2021.3098062.
  • [PDF] Alessandro Albini, Giorgio Cannata, Perla Maiolino, "A Local Filtering Technique For Robot Skin Data", IEEE Robotics and Automation Letters

  • [PDF] Tim Y. Tang, Daniele De Martini, Paul Newman, "Get to the Point: Learning Lidar Place Recognition and Metric Localisation Using Overhead Imagery", Proceedings of Robotics: Science and Systems, 2021.

  • [PDF] Tarlan Suleymanov, Matthew Gadd, Daniele De Martini, Paul Newman, "The Oxford Road Boundaries Dataset", in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Workshop on 3D-Deep Learning for Automated Driving (3D-DLAD), (Nagoya, Japan), July 2021

  • [PDF] Matthew Gadd, Daniele De Martini, Paul Newman, "Unsupervised Place Recognition with Deep Embedding Learning over Radar Videos", Workshop on Radar Perception for All-Weather Autonomy at the IEEE International Conference on Robotics and Automation (ICRA), 2021

  • [PDF] Scimeca, Luca, Josie Hughes, Perla Maiolino, Liang He, Thrishantha Nanayakkara, and Fumiya Iida., "Action Augmentation of Tactile Perception for Soft-Body Palpation", 2021

  • [PDF] Martin Engelcke, Oiwi Parker Jones, Ingmar Posner, "GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement", arXiv preprint: 2104.09958.

  • [PDF] Marc Rigter, Bruno Lacerda, Nick Hawes, "Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes", In Proceedings of the AAAI Conference on Artificial Intelligence, 2021.

  • [PDF] Rob Weston, Oiwi Parker-Jones, Ingmar Posner, "There and Back Again: Learning to Simulate Radar For Real World Applications", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Chia-Man Hung, Li Sun, Yizhe Wu, Ioannis Havoutis, Ingmar Posner, "Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Oliver Groth, Chia-Man Hung, Andrea Vedaldi, Ingmar Posner, "Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Rhys Howard, Sam Barrett, and Lars Kunze, "Don’t Blindly Trust Your CNN: Towards Competency-Aware Object Detection by Evaluating Novelty in Open-Ended Environments", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Mohamed Baioumy, Paul Duckworth, Bruno Lacerda and Nick Hawes, "Active Inference for Integrated State-Estimation, Control, and Learning", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Mohamed Baioumy, Corrado Pezzato, Riccardo Ferrari, Carlos H. Corbato and Nick Hawes, "Fault-tolerant Control of Robotic Systems with Sensory Faults using Decoupled Active Inference", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Traiko Dinev*, Wolfgang Merkt, Vladimir Ivan, Ioannis Havoutis, Sethu Vijayakumar, "Sparsity-Inducing Optimal Control via Differential Dynamic Programming", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Carlo Tiseo*, Vladimir Ivan, Wolfgang Merkt, Ioannis Havoutis, Michael Mistry, Sethu Vijayakumar, "A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Oliwier Aleksander Melon*, Romeo Orsolino, David Surovik, Mathieu Geisert, Ioannis Havoutis, Maurice Fallon, "Receding-Horizon Perceptive Trajectory Optimization for Dynamic Legged Locomotion with Learned Initialization", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Henrique Ferrolho*, Vladimir Ivan, Wolfgang Merkt, Ioannis Havoutis, Sethu Vijayakumar, "Inverse Dynamics vs. Forward Dynamics in Direct Transcription Formulations for Trajectory Optimization", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Siddhant Gangapurwala*, Mathieu Geisert, Romeo Orsolino, Maurice Fallon, Ioannis Havoutis, "Real-Time Trajectory Adaptation for Quadrupedal Locomotion using Deep Reinforcement Learning", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Wolfgang Merkt, Vladimir Ivan, Traiko Dinev, Ioannis Havoutis, Sethu Vijayakumar, "Memory Clustering using Persistent Homology for Multimodality- and Discontinuity-Sensitive Learning of Optimal Control Warm-starts", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Matias Mattamala, Milad Ramezani, Marco Camurri, Maurice Fallon, "Learning Camera Performance Models for Active Multi-Camera Visual Teach and Repeat", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Yiduo Wang, Nils Funk, Milad Ramezani, Sotiris Papatheodorou, Marija Popovic, Marco Camurri, Stefan Leutenegger, Maurice Fallon, "Elastic and Efficient LiDAR Reconstruction for Large-Scale Exploration Tasks", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Georgi Tinchev, Adrian Penate-Sanchez, Maurice Fallon, "SKD: Keypoint Detection for Point Clouds using Saliency Estimation", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] David Wisth, Marco Camurri, Sandipan Das, Maurice Fallon, "Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry", IEEE Intl. Conf. on Robotics and Automation (ICRA), 2021.

  • [PDF] Charlie Street, Sebastian Putz, Manuel Muhlig, Nick Hawes, Bruno Lacerda, "Congestion-Aware Policy Synthesis for Multi-Robot Systems", IEEE Transactions on Robotics, 2021.

  • [PDF] Mark Finean, Wolfgang Merkt, Ioannis Havoutis, "Predicted Composite Signed-Distance Fields for Real-Time Motion Planning in Dynamic Environments", International Conference on Automated Planning and Scheduling (ICAPS), 2021.

  • [PDF] Catherine A. Harris, Nick Hawes, Richard Dearden, "Online Plan Modification in Uncertain Resource-Constrained Environments",

  • [PDF] D. Williams, M. Gadd, D. De Martini, and P. Newman. “Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2021.

  • [PDF]Paper page J. D. Gammell and M. P. Strub. “Asymptotically optimal sampling-based motion planning methods,” Annual Review of Control, Robotics, and Autonomous Systems, 4(1). 2021. Invited.

2020

  • [PDF] M. Broome, M. Gadd, D. De Martini, and P. Newman, “On the Road: Route Proposal from Radar Self-Supervised by Fuzzy LiDAR Traversability,” AI, vol. 1, no. 4, pp. 558–58, 2020.

  • [PDF] Tim Y. Tang, Daniele De Martini, Shangzhe Wu, and Paul Newman, “Self-Supervised Localisation between Range Sensors and Overhead Imagery,” in RSS (Robotics: Science and Systems) 2020.
  • [PDF] P. Duckworth, B. Lacerda, and N. Hawes, “Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes,” in Conference on Robot Learning (CoRL), 2020.

  • [PDF] D. Surovik, O. Melon, M. Geisert, M. Fallon, and I. Havoutis, “Learning an Expert Skill-Space for Replanning Dynamic Quadruped Locomotion over Obstacles,” in Conference on Robot Learning (CoRL), 2020.

  • [PDF] A. L. Mitchell, M. Engelcke, O. Parker Jones, D. Surovik, S. Gangapurwala, O. Melon, I. Havoutis, and I. Posner, “First Steps: Latent-Space Control with Semantic Constraints for Quadruped Locomotion,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2020.
  • [PDF]Paper page R. Border and J. D. Gammell. “Proactive estimation of occlusions and scene coverage for planning next best views in an unstructured representation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 25 Oct. - 25 Nov. 2020.
  • [PDF]Paper page K. M. Judd and J. D. Gammell. “Occlusion-robust MVO: Multimotion estimation through occlusion via motion closure,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 25 Oct. - 25 Nov. 2020.

  • [PDF]Paper page M. Paton and M. P. Strub and T. Brown and R. J. Greene and J. Lizewski and V. Patel and J. D. Gammell and I. A. D. Nesnas. “Navigation on the line: Traversability analysis and path planning for extreme-terrain rappelling rovers,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 25 Oct. - 25 Nov. 2020. Best Safety, Security, and Rescue Robotics Paper Award Finalist.

  • [PDF] D. Barnes, M. Gadd, P. Murcutt, P. Newman, and I. Posner, “The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, 2020.

  • [PDF] M. Engelcke, A. R. Kosiorek, O. Parker Jones, and I. Posner, “GENESIS: Generative Scene Inference and Sampling of Object-Centric Latent Representations,” International Conference on Learning Representations (ICLR), 2020.

  • [PDF] M. Rigter, B. Lacerda, and N. Hawes, “A Framework for Learning from Demonstration with Minimal Human Effort,” Robotics and Automation Letters (RA-L), 2020.

  • [PDF] S. Saftescu, M. Gadd, D. De Martini, D. Barnes, and P. Newman, “Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, 2020.

  • [PDF] D. Barnes and I. Posner, “Under the Radar: Learning to Predict Robust Keypoints for Odometry Estimation and Metric Localisation in Radar,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Paris, 2020.

  • [PDF] [DOI] T. Y. Tang, D. De Martini, D. Barnes, and P. Newman, “RSL-Net: Localising in Satellite Images From a Radar on the Ground,” IEEE Robotics and Automation Letters, vol. 5, iss. 2, pp. 1087-1094, 2020.

  • [PDF] C. Street, B. Lacerda, M. Mühlig, and N. Hawes, “Multi-Robot Planning Under Uncertainty with Congestion-Aware Models,” in 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Auckland, New Zealand, 2020.

  • [PDF] W. Maddern, G. Pascoe, M. Gadd, D. Barnes, B. Yeomans, and P. Newman, “Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset,” arXiv preprint arXiv: 2002.10152, 2020.

  • [PDF] M. Ramezani, G. Tinchev, E. Iuganov, and M. Fallon, “Online LiDAR-SLAM for Legged Robots with Robust Registration and Deep-Learned Loop Closure,” in IEEE Robotics and Automation Letters, 2020.

  • [PDF] O. Melon, M. Geisert, D. Surovik, I. Havoutis, and M. Fallon, “Reliable Trajectories for Dynamic Quadrupeds using Analytical Costs and Learned Initializations,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), 2020.

  • [PDF] Y. Wang, M. Ramezani, and M. Fallon, “Actively Mapping Industrial Structures with Information Gain-Based Planning on a Quadruped Robot,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), 2020.

  • [PDF] D. Wisth, M. Camurri, and M. Fallon, “Preintegrated Velocity Bias Estimation to Overcome Contact Nonlinearities in Legged Robot Odometry,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), 2020.

  • [PDF] M. Brandao, O. B. Aladag, and I. Havoutis, “GaitMesh: controller-aware navigation meshes for long-range legged locomotion planning in multi-layered environments,” IEEE Robotics and Automation Letters, 2020.

  • [PDF] S. Gangapurwala, A. Mitchell, and I. Havoutis, “Guided Constrained Policy Optimization for Dynamic Quadrupedal Robot Locomotion,” IEEE Robotics and Automation Letters, 2020.

  • [PDF] M. Gadd, D. De Martini, and P. Newman, “Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance,” in IEEE/ION Position, Location and Navigation Symposium (PLANS), Portland, OR, USA, 2020.

  • [PDF] T. Suleymanov, M. Gadd, L. Kunze, and P. Newman, “LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic,” in IEEE/ION Position, Location and Navigation Symposium (PLANS), Portland, OR, USA, 2020.

  • [PDF] C. Street, “Towards Multi-Robot Coordination under Temporal Uncertainty,” in 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Auckland, New Zealand, 2020.

  • [PDF] M. Brandao and I. Havoutis, “Learning Sequences of Approximations for Hierarchical Motion Planning,” International Conference on Automated Planning and Scheduling (ICAPS), 2020.

  • [PDF] C. Azevedo, B. Lacerda, N. Hawes, and P. Lima, “Long-Run Multi-Robot Planning With Uncertain Task Durations,” in 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020.

  • [PDF] M. Painter, B. Lacerda, and N. Hawes, “Convex Hull Monte-Carlo Tree Search,” in The International Conference on Automated Planning and Scheduling (ICAPS), 2020.

  • [PDF] P. Kaul, D. De Martini, M. Gadd, and P. Newman, “RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Las Vegas, NV, USA, 2020.

  • [PDF] M. Gadd, D. De Martini, L. Marchegiani, L. Kunze, and P. Newman, “Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Workshop on Ensuring and Validating Safety for Automated Vehicles (EVSAV), 2020.

  • [DOI] M. Baioumy, M. Mattamala, P. Duckworth, B. Lacerda, and N. Hawes, “Adaptive Manipulator Control using Active Inference with Precision Learning,” in UKRAS20 Conference: “Robots into the real world” Proceedings, Lincoln, United Kingdom, 2020.

  • [PDF] D. Williams, D. De Martini, M. Gadd, L. Marchegiani, and P. Newman, “Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision,” in IEEE Intelligent Transportation Systems Conference (ITSC), Rhodes, Greece, 2020.

  • [PDF] M. Baioumy, M. Mattamala, and N. Hawes, “Variational Inference for Predictive and Reactive Controllers,” in ICRA 2020 Workshop on New advances in Brain-inspired Perception, Interaction and Learning, Paris, France, 2020.

  • Paper pageM. P. Strub and J. D. Gammell, “Adaptively Informed Trees (AIT*): Fast Asymptotically Optimal Path Planning through Adaptive Heuristics,” in IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.

  • Paper page M. P. Strub and J. D. Gammell, “Advanced BIT* (ABIT*): Sampling-Based Planning with Advanced Graph-Search Techniques,” in IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.

  • [PDF] S. Chadwick and P. Newman, “Radar as a Teacher: Weakly Supervised Vehicle Detection using Radar Labels,” in IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.

  • [PDF] L. Scimeca, F. Iida, and P. Maiolino, “Efficient Bayesian Exploration for Soft Morphology-Action Co-Optimization,” in IEEE International Conference on Soft Robotics (RoboSoft), 2020.

  • [PDF] J. Hughes, P. Maiolino, T. Nanayakkara, and F. Iida, “Sensorized Phantom For Characterizing Large Area Deformation of Soft Bodies for Medical Applications,” in IEEE International Conference on Soft Robotics (RoboSoft), 2020.

  • L. Scimeca, P. Maiolino, E. Bray, and F. Iida, “Structuring of Tactile Sensory Information for Category Formation in Robotics Palpation,” Autonomous Robots Journal (Springer), 2020.

  • [PDF] C. Mastalli, I. Havoutis, M. Focchi, D. G. Caldwell, and C. Semini, “Motion Planning for Quadrupedal Locomotion: Coupled Planning, Terrain Mapping and Whole-Body Control,” , 2020.

  • [PDF] M. Budd, B. Lacerda, P. Duckworth, A. West, B. Lennox, and N. Hawes, “Markov Decision Processes with Unknown State Feature Values for Safe Exploration using Gaussian Processes,” in Proc. of the 2020 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2020.

  • [PDF] C. Azevedo, B. Lacerda, N. Hawes, and P. Lima, “Long-Run Multi-Robot Planning under Uncertain Action Durations for Persistent Tasks,” in Proc. of the 2020 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2020.

  • [PDF] M. Tomy, B. Lacerda, N. Hawes, and J. L. Wyatt, “Battery Charge Scheduling in Long-Life Autonomous Mobile Robots via Multi-Objective Decision Making Under Uncertainty,” Robotics and Autonomous Systems, vol. 133, 2020.

  • [PDF] L. Sintini and L. Kunze, “Semi-Supervised Novelty Detection in Opportunistic Science Missions using Variational Autoencoders,” in Proceedings of the British Machine Vision Conference (BMVC), 2020.

  • [PDF] J. Ocón, I. Dragomir, A. Coles, A. Green, L. Kunze, R. Marc, C.J. Perez , T. Germa, V. Bissonnette, G. Scalise, and M. Foughali, "ADE: Autonomous DEcision making in very long traverses," in International Symposium on Artificial Intelligence, Robotics and Automation in Space (I-SAIRAS), 2020.

2019

  • [PDF] E. Wagstaff, F. Fuchs, M. Engelcke, I. Posner, and M. A. Osborne, “On the Limitations of Representing Functions on Sets,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019, p. 6487–6494.

  • [PDF] G. Tinchev, A. Penate-Sanchez, and M. Fallon, “Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU,” IEEE Robotics and Automation Letters, 2019.

  • [PDF] S. Cen and P. Newman, “Radar-only ego-motion estimation in difficult settings via graph matching,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

  • [PDF] M. Geisert, T. Yates, A. Orgen, P. Fernbach, and I. Havoutis, “Contact Planning for the ANYmal Quadruped Robot using an Acyclic Reachability-Based Planner,” in Towards Autonomous Robotic Systems Conference (TAROS), 2019.

  • Paper page K. Judd and J. Gammell, “The Oxford Multimotion Dataset: Multiple SE(3) motions with ground truth.” 2019.

  • [PDF] R. Aldera, D. De Martini, M. Gadd, and P. Newman, “Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

  • [PDF] B. Lacerda, F. Faruq, D. Parker, and N. Hawes, “Probabilistic planning with formal performance guarantees for mobile service robots,” International Journal of Robotics Research, 2019.

  • [PDF] M. Mansouri, B. Lacerda, N. Hawes, and F. Pecora, “Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints,” in Proceedings of the 2019 International Joint Conference on Artificial Intelligence (IJCAI), Macau, China, 2019.

  • [PDF] H. Porav, T. Bruls, and P. Newman, “I Can See Clearly Now: Image Restoration via De-Raining,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

  • [PDF] R. Weston, S. Cen, P. Newman, and I. Posner, “Probably Unknown: Deep Inverse Sensor Modelling Radar,” in IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

  • [PDF] S. Chadwick, W. Maddern, and P. Newman, “Distant Vehicle Detection Using Radar and Vision,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

  • [PDF] H. Porav and P. Newman, “Imminent Collision Mitigation with Reinforcement Learning and Vision,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.

  • [PDF] T. Bruls, H. Porav, L. Kunze, and P. Newman, “The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV) Paris, France. June 9-12, 2019, 2019.

  • [PDF] D. Wisth, M. Camurri, and M. Fallon, “Robust Legged Robot State Estimation Using Factor Graph Optimization,” in IEEE Robotics and Automation Letters, 2019.

  • [PDF] G. Tinchev, A. Penate~Sanchez, and M. Fallon, “Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU,” in IEEE Robotics and Automation Letters, 2019.

  • [PDF] C. Rauch, V. Ivan, T. Hospedales, J. Shotton, and M. Fallon, “Learning Driven Coarse-to-Fine Articulated Robot Tracking,” in IEEE International Conference on Robotics and Automation (ICRA), 2019.

  • [PDF] M. Geisert, T. Yates, A. Orgen, P. Fernbach, and I. Havoutis, “Contact Planning for the ANYmal Quadruped Robot using an Acyclic Reachability-Based Planner,” in Towards Autonomous Robotic Systems Conference (TAROS), 2019.

  • [PDF] M. Brandao, M. Fallon, and I. Havoutis, “Multi-controller multi-objective locomotion planning for legged robots,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.

  • [PDF] S. Ishida, M. Rigter, and N. Hawes, “Robot Path Planning for Multiple Target Regions,” in Proceedings of the 2019 European Conference on Mobile Robots (ECMR), Prague, Czech Republic, 2019.

  • [PDF] M. Mansouri, B. Lacerda, N. Hawes, and F. Pecora, “Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints,” in ICRA 2019 Workshop on Resilient Robot Teams: Composing, Acting, and Learning, Montreal, Canada, 2019.

  • [PDF] M. Tomy, B. Lacerda, N. Hawes, and J. Wyatt, “Battery Charge Scheduling in Long-Life Autonomous Mobile Robots,” in Proceedings of the 2019 European Conference on Mobile Robots (ECMR), Prague, Czech Republic, 2019.

  • [PDF] R. Aldera, D. De Martini, M. Gadd, and P. Newman, “What Could Go Wrong? Introspective Radar Odometry in Challenging Environments,” in IEEE Intelligent Transportation Systems (ITSC) Conference, Auckland, New Zealand, 2019.

  • [PDF] S. Kyberd, J. Attias, P. Get, P. Murcutt, C. Prahacs, M. Towlson, S. Venn, A. Vasconcelos, M. Gadd, D. De Martini, and P. Newman, “The Hulk: Design and Development of a Weather-proof Vehicle for Long-term Autonomy in Outdoor Environments,” in International Conference on Field and Service Robotics (FSR), Tokyo, Japan, 2019.

  • [PDF] D. Barnes, R. Weston, and I. Posner, “Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information,” in Conference on Robot Learning (CoRL), 2019.

  • [PDF] B. Lacerda and P. U. Lima, “Petri net based multi-robot task coordination from temporal logic specifications,” Robotics and Autonomous Systems, vol. 122, 2019.

  • [PDF] Y. Wu, S. Kasewa, O. Groth, S. Salter, L. Sun, O. P. Jones, and I. Posner, “Imagine That! Leveraging Emergent Affordances for Tool Synthesis in Reaching Tasks,” arXiv preprint arXiv:1909.13561, 2019.

  • [PDF] F. Fuchs, A. Kosiorek, L. Sun, O. Parker Jones, and I. Posner, “End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning,” in Sets and Parts Workshop at the Conference on Neural Information Processing Systems (NeurIPS), 2019.

  • [PDF] F. Fuchs, O. Groth, A. Kosiorek, A. Bewley, M. Wulfmeier, A. Vedaldi, and I. Posner, “Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes,” in Proceedings of the British Machine Vision Conference (BMVC), 2019.

  • [PDF] T. Suleymanov, L. Kunze, and P. Newman, “Online Inference and Detection of Curbs in Partially Occluded Scenes with Sparse LIDAR,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Auckland, New Zealand, 2019.

  • [PDF] T. Bruls, H. Porav, L. Kunze, and P. Newman, “Generating All the Roads to Rome: Road Layout Randomization for Improved Road Marking Segmentation,” in 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, p. 831–838.

  • [PDF] H. Porav, T. Bruls, and P. Newman, “Don’t worry about the weather: Unsupervised condition-dependent domain adaptation,” in 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, p. 33–40.

  • [PDF] H. Porav, V. Musat, and P. Newman, “Reducing Steganography In Cycle-consistency GANs,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019, p. 78–82.

  • [PDF] M. R. Balme, M. C. Curtis-Rouse, S. Banham, D. Barnes, R. Barnes, A. Bauer, C. C. Bedford, J. C. Bridges, F. E. G. Butcher, P. Caballo, A. Caldwell, A. J. Coates, C. Cousins, J. M. Davis, J. Dequaire, P. Edwards, P. Fawdon, K. Furuya, M. Gadd, P. Get, A. Griffiths, P. M. Grindrod, M. Gunn, S. Gupta, R. Hansen, J. K. Harris, L. J. Hicks, J. Holt, B. Huber, C. Huntly, I. Hutchinson, L. Jackson, S. Kay, S. Kyberd, H. N. Lerman, M. McHugh, W. J. McMahon, J. P. Muller, T. Ortner, G. Osinski, G. Paar, L. J. Preston, S. P. Schwenzer, R. Stabbins, Y. Tao, C. Traxler, S. Turner, L. Tyler, S. Venn, H. Walker, T. Wilcox, J. Wright, and B. Yeomans, “The 2016 UK Space Agency Mars Utah Rover Field Investigation (MURFI),” Planetary and Space Science, vol. 165, pp. 31-56, 2019.

2018

  • [PDF] P. Amayo, T. Bruls, and P. Newman, “Semantic Classification of Road Markings from Geometric Primitives,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, 2018.

  • [PDF] T. Bruls, W. Maddern, A. A. Morye, and P. Newman, “Mark Yourself: Road Marking Segmentation via Weakly-Supervised Annotations from Multimodal Data,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.

  • [PDF] T. Suleymanov, P. Amayo, and P. Newman, “Inferring Road Boundaries Through and Despite Traffic,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, 2018.

  • [PDF] L. Kunze, T. Bruls, T. Suleymanov, and P. Newman, “Reading between the Lanes: Road Layout Reconstruction from Partially Segmented Scenes,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, 2018.

  • [PDF] G. Tinchev, S. Nobili, and M. Fallon, “Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments,” in Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.

  • [PDF] C. Gurau, A. Bewley, and I. Posner, “Dropout Distillation for Efficiently Estimating Model Confidence,” arXiv preprint arXiv:1809.10562, 2018.

  • [PDF] L. Marchegiani and I. Posner, “Long-Term Driving Behaviour Modelling for Driver Identification,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), Maui, Hawaii, USA, 2018.

  • [PDF] F. Faruq, B. Lacerda, D. Parker, and N. Hawes, “Simultaneous Task Allocation and Planning Under Uncertainty,” in Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.

  • [PDF] O. Groth, F. B. Fuchs, I. Posner, and A. Vedaldi, “ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking,” in The European Conference on Computer Vision (ECCV), 2018.

  • [PDF] L. Kunze, T. Bruls, T. Suleymanov, and P. Newman, “Reading between the Lanes: Road Layout Reconstruction from Partially Segmented Scenes (Extended Abstract),” in Robotics Science and Systems (RSS) Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models, 2018.

  • [PDF] A. R. Kosiorek, H. Kim, I. Posner, and Y. W. Teh, “Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects,” arXiv preprint arXiv:1806.01794, 2018.

  • [PDF] T. A. Le, A. R. Kosiorek, N. Siddharth, Y. W. Teh, and F. Wood, “Revisiting Reweighted Wake-Sleep,” arXiv preprint arXiv:1805.10469, 2018.

  • [PDF] B. Lacerda, D. Parker, and N. Hawes, “Policy Generation with Probabilistic Guarantees for Long-term Autonomy of a Mobile Robot,” in Proceedings of the International Workshop on the Verification and Validation of Autonomous Systems (VaVAS), Oxford, United Kingdom, 2018.

  • [PDF] P. Amayo, P. Piniés, L. M. Paz, and P. Newman, “Fast Global Labelling For Depth-Map Improvement Via Architectural Priors,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.

  • [PDF] P. Amayo, P. Piniés, L. M. Paz, and P. Newman, “Geometric Multi-Model Fitting with a Convex Relaxation Algorithm,” in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, 2018.

  • [PDF] L. Marchegiani and P. Newman, “Learning to listen to your ego(-motion) : Metric Motion Estimation from Auditory Signals,” in Towards Autonomous Robotics Systems (TAROS), 2018.

  • [PDF] [DOI] I. Havoutis and S. Calinon, “Learning from demonstration for semi-autonomous teleoperation,” Autonomous Robots, 2018.

  • [PDF] T. Rainforth, A. R. Kosiorek, T. A. Le, C. J. Maddison, M. Igl, F. Wood, and Y. W. Teh, “Tighter Variational Bounds are Not Necessarily Better,” arXiv preprint arXiv:1802.04537, 2018.

  • [PDF] N. Dhir, H. Dallali, E. M. Ficanha, G. A. Ribeiro, and M. Rastgaar, “Locomotion Envelopes for Adaptive Control of Powered Ankle Prostheses,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Brisbane, 2018.

  • Paper page R. Border, J. D. Gammell, and P. Newman, “Surface Edge Explorer (SEE): Planning Next Best Views Directly from 3D Observations,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, 2018.

  • [PDF] S. Nobili, G. Tinchev, and M. Fallon, “Predicting Alignment Risk to Prevent Localization Failure,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Brisbane, 2018.

  • [PDF] C. Rauch, T. Hospedales, J. Shotton, and M. Fallon, “Visual Articulated Tracking in the Presence of Occlusions,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Brisbane, 2018.

  • [PDF] R. Scona, M. Jaimez, Y. R. Petillot, M. Fallon, and D. Cremers, “StaticFusion: Background Reconstruction for Dense RGB-D SLAM in Dynamic Environments,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Brisbane, 2018.

  • Paper page J. D. Gammell, T. D. Barfoot, and S. S. Srinivasa, “Informed Sampling for Asymptotically Optimal Path Planning,” IEEE Transactions on Robotics (T-RO), 2018.

  • [PDF] P. Marion, M. Fallon, R. Deits, A. Valenzuela, C. P. D’Arpino, G. Izatt, L. Manuelli, M. Antone, H. Dai, T. Koolen, J. Carter, S. Kuindersma, and R. Tedrake, “Director: A User Interface Designed for Robot Operation With Shared Autonomy,” Chapter in The DARPA Robotics Challenge Finals: Humanoid Robots To The Rescue, 2018.

  • [PDF] [DOI] M. J. A. Zeestraten, I. Havoutis, and S. Calinon, “Programming by Demonstration for Shared Control with an Application in Teleoperation,” IEEE Robotics and Automation Letters (RA-L), 2018.

  • [PDF] M. Gadd and P. Newman, “The Data Market: Policies for Decentralised Visual Localisation,” ArXiv e-prints, 2018.

  • [PDF] D. Barnes, W. Maddern, G. Pascoe, and I. Posner, “Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, 2018.

  • Paper page K. M. Judd, J. D. Gammell, and P. Newman, “Multimotion Visual Odometry (MVO): Simultaneous Estimation of Camera and Third-Party Motions,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018.

  • J. Lee, Y. Lee, J. Kim, A. R. Kosiorek, S. Choi, and Y. W. Teh, Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks, 2018.

  • [PDF] K. Shiarlis, M. Wulfmeier, S. Salter, S. Whiteson, and I. Posner, “TACO: Learning Task Decomposition via Temporal Alignment for Control,” Proceedings of the 35th International Conference on Machine Learning, 2018.

  • [PDF] S. H. Cen and P. Newman, “Precise Ego-Motion Estimation with Millimeter-Wave Radar under Diverse and Challenging Conditions,” Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018.

  • [PDF] F. Jovan, J. L. Wyatt, and N. Hawes, “Efficient Bayesian Methods for Counting Processes in Partially Observable Environments,” in The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), 2018.

  • [PDF] L. Kunze, H. Karaoguz, J. Young, F. Jovan, J. Folkesson, P. Jensfelt, and N. Hawes, “SOMA: A Framework for Understanding Change in Everyday Environments Using Semantic Object Maps,” in In Papers from the 2018 AAAI Fall Symposium on Reasoning and Learning in Real-World Systems for Long-Term Autonomy., 2018.

  • [PDF] L. Kunze, N. Hawes, T. Duckett, M. Hanheide, and T. Krajnik, “Artificial Intelligence for Long-Term Robot Autonomy: A Survey,” in IEEE Robotics and Automation Letters, 2018.

  • [PDF] M. Wulfmeier, A. Bewley, and I. Posner, “Incremental Adversarial Domain Adaptation for Continually Changing Environments,” in IEEE International Conference on Robotics and Automation (ICRA), 2018.

  • [PDF] M. Fallon, “Accurate and robust localization for walking robots fusing kinematics, inertial, vision and LIDAR,” in Interface Focus, Royal Society, London, 2018.

  • [PDF] M. Tanner, S. Saftescu, A. Bewley, and P. Newman, “Meshed Up: Learnt Error Correction in 3D Reconstructions,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, p. 3201–3206.

  • [PDF] H. Porav, W. Maddern, and P. Newman, “Adversarial training for adverse conditions: Robust metric localisation using appearance transfer,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, p. 1011–1018.

2017

  • [PDF] N. Dhir, A. R. Kosiorek, and I. Posner, “Bayesian Delay Embeddings for Dynamical Systems,” in NIPS Timeseries Workshop, 2017.

  • [PDF] M. J. A. Zeestraten, I. Havoutis, S. Calinon, and D. G. Caldwell, “Learning Task-Space Synergies using Riemannian Geometry,” in Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.

  • [PDF] M. Wulfmeier, I. Posner, and P. Abbeel, “Mutual Alignment Transfer Learning,” in Conference on Robot Learning, 2017.

  • [PDF] C. Florensa, D. Held, M. Wulfmeier, and P. Abbeel, “Reverse Curriculum Generation for Reinforcement Learning,” in Conference on Robot Learning, 2017.

  • [PDF] A. R. Kosiorek, A. Bewley, and I. Posner, “Hierarchical Attentive Recurrent Tracking,” in Neural Information Processing Systems, 2017.

  • [PDF] T. Sattler, W. Maddern, A. Torii, J. Sivic, T. Pajdla, M. Pollefeys, and M. Okutomi, “Benchmarking 6DOF Urban Visual Localization in Changing Conditions,” ArXiv e-prints, 2017.

  • [PDF] [DOI] M. Wulfmeier, D. Rao, D. Z. Wang, P. Ondruska, and I. Posner, “Large-scale cost function learning for path planning using deep inverse reinforcement learning,” The International Journal of Robotics Research, p. 278364917722396, 2017.

  • [PDF] C. Gurau, D. Rao, C. H. Tong, and I. Posner, “Learn from Experience: Probabilistic Prediction of Perception Performance to Avoid Failure,” The International Journal of Robotics Research, 2017.

  • [PDF] J. Hawke, A. Bewley, and I. Posner, “What Makes a Place? Building Bespoke Place Dependent Object Detectors for Robotics,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017.

  • [PDF] M. Wulfmeier, A. Bewley, and I. Posner, “Addressing Appearance Change in Outdoor Robotics with Adversarial Domain Adaptation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017.

  • [PDF] R. Scona, S. Nobili, Y. Petillot, and M. Fallon, “Direct Visual SLAM Fusing Proprioception for a Humanoid Robot,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.

  • [PDF] J. Dequaire, P. Ondrúška, D. Rao, D. Wang, and I. Posner, “Deep tracking in the wild: End-to-end tracking using recurrent neural networks,” The International Journal of Robotics Research, 2017.

  • [PDF] B. Yeomans, H. Porav, M. Gadd, D. Barnes, J. Dequaire, T. Wilcox, S. Kyberd, S. Venn, and P. Newman, “MURFI 2016 – From Cars to Mars: Applying Autonomous Vehicle Navigation Methods To a Space Rover Mission,” in Proceedings of the 14th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA), Leiden, Netherlands, 2017.

  • [PDF] P. Amayo, P. Pinies, L. M. Paz, and P. Newman, “Geometric Multi-Model Fitting with a Convex Relaxation Algorithm,” ArXiv e-prints, 2017.

  • [PDF] G. Pascoe, W. Maddern, M. Tanner, P. Pinies, and P. Newman, “NID-SLAM: Robust Monocular SLAM using Normalised Information Distance,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, 2017.

  • [PDF] S. Nobili, M. Camurri, V. Barasuol, M. Focchi, D. Caldwell, C. Semini, and M. Fallon, “Heterogeneous Sensor Fusion for Accurate State Estimation of Dynamic Legged Robots,” in Robotics: Science and Systems (RSS), Cambridge, MA, 2017.

  • [PDF] C. Mastalli, M. Focchi, I. Havoutis, A. Radulescu, S. Calinon, J. Buchli, D. G. Caldwell, and C. Semini, “Trajectory and Foothold Optimization using Low-Dimensional Models for Rough Terrain Locomotion,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Singapore, 2017.

  • [PDF] M. Camurri, M. Fallon, S. Bazeille, A. Radulescu, V. Barasuol, D. G. Caldwell, and C. Semini, “Probabilistic Contact Estimation and Impact Detection for State Estimation of Quadruped Robots.” 2017, pp. 1023-1030.

  • [PDF] A. Radulescu, I. Havoutis, D. G. Caldwell, and C. Semini, “Whole-body Trajectory Optimization for Non-periodic Dynamic Motions on Quadrupedal Systems,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Singapore, 2017.

  • [PDF] [DOI] M. J. A. Zeestraten, I. Havoutis, J. Silvério, S. Calinon, and D. G. Caldwell, “An Approach for Imitation Learning on Riemannian Manifolds,” IEEE Robotics and Automation Letters (RA-L), vol. 2, iss. 3, p. 1240–1247, 2017.

  • [PDF] I. Havoutis and S. Calinon, “Supervisory teleoperation with online learning and optimal control,” in Proc. IEEE Intl Conf. on Robotics and Automation (ICRA), Singapore, 2017.

  • [PDF] S. Nobili, R. Scona, M. Caravagna, and M. Fallon, “Overlap-based ICP Tuning for Robust Localization of a Humanoid Robot,” in IEEE Intl. Conf. on Robotics and Automation (ICRA), Singapore, 2017.

  • [PDF] M. Engelcke, D. Rao, D. Zeng Wang, C. Hay Tong, and I. Posner, “Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2017.

  • [PDF] [DOI] W. Maddern, G. Pascoe, C. Linegar, and P. Newman, “1 Year, 1000 km: The Oxford RobotCar dataset,” The International Journal of Robotics Research, vol. 36, iss. 1, p. 3–15, 2017.

  • [PDF] D. Barnes, W. Maddern, and I. Posner, “Find Your Own Way: Weakly-Supervised Segmentation of Path Proposals for Urban Autonomy,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

  • [PDF] L. Marchegiani and I. Posner, “Leveraging the Urban Soundscape: Auditory Perception for Smart Vehicles,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

  • [PDF] M. R. Balme, M. C. Curtis-Rouse, S. Banham, D. Barnes, R. Barnes, A. Bauer, C. Bedford, J. Bridges, F. E. G. Butcher, P. Caballo, A. Caldwell, A. Coates, C. Cousins, J. Davis, J. Dequaire, P. Edwards, P. Fawdon, K. Furuya, M. Gadd, P. Get, A. Griffiths, P. M. Grindrod, M. Gunn, S. Gupta, R. Hansen, J. K. Harris, J. Holt, B. Huber, C. Huntly, I. Hutchinson, L. Jackson, S. Kay, S. Kybert, H. N. Lerman, M. McHugh, W. McMahon, J. P. Muller, G. Paar, L. J. Preston, S. Schwenzer, R. Stabbins, Y. Tao, C. Traxler, S. Turner, L. Tyler, S. Venn, H. Walker, J. Wright, and B. Yeomans, “UK Space Agency Mars Utah Rover Field Investigation 2016 (MURFI 2016): Overview of mission, aims and progress,” in 48th Lunar and Planetary Science Conference (LPSC), The Woodlands, TX, USA, 2017.

2016

  • [PDF] D. Withers and P. Newman, “Modelling Scene Change for Large-Scale Long Term Laser Localisation,” in International Conference on Robotics and Automation, ICRA, 2016.

  • [PDF] M. Wulfmeier, D. Rao, and I. Posner, “Incorporating Human Domain Knowledge into Large Scale Cost Function Learning,” in Neural Information Processing Systems Conference, Deep Reinforcement Learning Workshop, 2016.

  • [PDF] J. Dequaire, D. Rao, P. Ondruska, D. Zeng Wang, and I. Posner, “Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks,” ArXiv e-prints, 2016.

  • [PDF] O. Bartlett, C. Gurau, L. Marchegiani, and I. Posner, “Enabling Intelligent Energy Management for Robots using Publicly Available Maps,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016.

  • [PDF] C. Gurau, C. H. Tong, and I. Posner, “Fit for purpose? Predicting Perception Performance based on Past Experience,” in International Symposium on Experimental Robotics (ISER), Tokyo, Japan, 2016.

  • [PDF] W. Maddern and P. Newman, “Real-time probabilistic fusion of sparse 3D LIDAR and dense stereo,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016.

  • [PDF] M. Wulfmeier, D. Z. Wang, and I. Posner, ” Watch This: Scalable Cost-Function Learning for Path Planning in Urban Environments ,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016.

  • [PDF] T. Suleymanov, L. M. Paz, P. Piniés, G. Hester, and P. Newman, “The Path Less Taken: A Fast Variational Approach for Scene Segmentation Used for Closed Loop Control,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016.

  • [PDF] M. Gadd and P. Newman, “Checkout My Map: Version Control for Fleetwide Visual Localisation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016, pp. 5729-5736.

  • [PDF] L. M. Paz, T. Suleymanov, P. Piniés, G. Hester, and P. Newman, “On-line Scene Understanding for Closed Loop Control,” in Robotics: Science and Systems, Workshop on Geometry and Beyond: Representations, Physics, and Scene Understanding for Robotics, 2016.

  • [PDF] P. Ondruska, J. Dequaire, D. Zeng Wang, and I. Posner, “End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks,” in Robotics: Science and Systems, Workshop on Limits and Potentials of Deep Learning in Robotics, 2016.

  • [PDF] M. Tanner, P. Piniés, L. M. Paz, and P. Newman, “Keep Geometry in Context: Using Contextual Priors for Very-Large-Scale 3D Dense Reconstructions,” in Robotics: Science and Systems, Workshop on Geometry and Beyond: Representations, Physics, and Scene Understanding for Robotics, 2016.

  • [PDF] U. Schwesinger, M. Bürki, J. Timpner, S. Rottmann, L. Wolf, L. M. Paz, H. Grimmett, I. Posner, P. Newman, C. Häne, L. Heng, G. H. Lee, T. Sattler, M. Pollefeys, M. Allodi, F. Valenti, K. Mimura, B. Goebelsmann, and R. Siegwart, “Automated Valet Parking and Charging for e-Mobility–-Results of the V-Charge Project,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Gothenburg, Sweden, 2016.

  • [PDF] P. Ondruska, J. Dequaire, Zeng Wang Dominic, and I. Posner, “End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks,” ArXiv e-prints, 2016.

  • [PDF] M. Tanner, P. Piniés, L. M. Paz, and P. Newman, “DENSER Cities: A System for Dense Efficient Reconstructions of Cities,” ArXiv e-prints, 2016.

  • [PDF] J. Dequaire, C. H. Tong, W. Churchill, and I. Posner, “Off the Beaten Track: Predicting Localisation Performance in Visual Teach and Repeat,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

  • [PDF] P. Amayo, P. Piniés, L. M. Paz, and P. Newman, “A Unified Representation for Application of Architectural Constraints in Large-Scale Mapping,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

  • [PDF] T. Scott, A. A. Morye, P. Piniés, L. M. Paz, I. Posner, and P. Newman, “Choosing a Time and Place for Calibration of Lidar-Camera Systems,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

  • [PDF] C. Linegar, W. Churchill, and P. Newman, “Made to Measure: Bespoke Landmarks for 24-Hour, All-Weather Localisation with a Camera,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

  • [PDF] M. Tanner, P. Piniés, L. M. Paz, and P. Newman, “What Lies Behind: Recovering Hidden Shape in Dense Mapping,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

  • [PDF] P. Ondruska, “Neural Robotics – A New Perspective,” AAAI 2016 Robotics Fellowship, Phoenix, Arizona USA 2016.

  • [PDF] P. Ondruska and I. Posner, “Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks,” in The Thirtieth AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona USA, 2016.

2015

  • [PDF] [DOI] B. Mathibela, P. Newman, and I. Posner, “Reading the Road: Road Marking Classification and Interpretation,” IEEE Trans. Intelligent Transportation Systems, vol. 16, iss. 4, p. 2072–2081, 2015.

  • [DOI] S. Lowry, N. Sunderhauf, P. Newman, J. J. Leonard, D. Cox, P. Corke, and M. J. Milford, “Visual Place Recognition: A Survey,” Robotics, IEEE Transactions on, vol. PP, iss. 99, pp. 1-19, 2015.

  • [PDF] M. Wulfmeier, P. Ondruska, and I. Posner, “Maximum Entropy Deep Inverse Reinforcement Learning,” in Neural Information Processing Systems Conference, Deep Reinforcement Learning Workshop, Montreal, Canada, 2015.

  • [PDF] G. Pascoe, W. Maddern, and P. Newman, “Direct Visual Localisation and Calibration for Road Vehicles in Changing City Environments,” in IEEE International Conference on Computer Vision: Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving, Santiago, Chile, 2015.

  • [PDF] [DOI] C. McManus, B. Upcroft, and P. Newman, “Learning Place-Dependant Features for Long-Term Vision-Based Localisation,” Autonomous Robots, Special issue on Robotics Science and Systems 2014, pp. 1-25, 2015.

  • [PDF] P. Ondruska, P. Kohli, and S. Izadi, “MobileFusion: Real-time Volumetric Surface Reconstruction and Dense Tracking On Mobile Phones,” in International Symposium on Mixed and Augmented Reality (ISMAR), Fukuoka, Japan, 2015.

  • [PDF] A. Kumar, O. Irsoy, J. Su, J. Bradbury, R. English, B. Pierce, P. Ondruska, I. Gulrajani, and R. Socher, “Ask Me Anything: Dynamic Memory Networks for Natural Language Processing,” arXiv, 2015.

  • [PDF] G. Pascoe, W. Maddern, and P. Newman, “Robust Direct Visual Localisation using Normalised Information Distance,” in British Machine Vision Conference (BMVC), Swansea, Wales, 2015.

  • [PDF] T. Scott, A. A. Morye, P. Piniés, L. M. Paz, I. Posner, and P. Newman, “Exploiting Known Unknowns: Scene Induced Cross-Calibration of Lidar-Stereo Systems,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015.

  • [PDF] H. Grimmett, R. Triebel, R. Paul, and I. Posner, “Introspective Classification for Robot Perception,” International Journal of Robotics Research (IJRR), 2015.

  • [PDF] D. Barnes, W. Maddern, and I. Posner, “Exploiting 3D Semantic Scene Priors for Online Traffic Light Interpretation,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Seoul, South Korea, 2015.

  • [PDF] J. Hawke, C. Gurau, C. H. Tong, and I. Posner, “Wrong Today, Right Tomorrow: Experience-Based Classification for Robot Perception,” in Field and Service Robotics (FSR), Toronto, ON, Canada, 2015.

  • [PDF] P. Piniés, L. M. Paz, and P. Newman, “Dense and Swift Mapping with Monocular Vision,” in International Conference on Field and Service Robotics (FSR), Toronto, ON, Canada, 2015.

  • [PDF] M. Tanner, P. Piniés, L. M. Paz, and P. Newman, “BOR2G: Building Optimal Regularised Reconstructions with GPUs (in cubes),” in International Conference on Field and Service Robotics (FSR), Toronto, ON, Canada, 2015.

  • [PDF] P. Nelson, C. Linegar, and P. Newman, “Building, Curating, and Querying Large-scale Data Repositories for Field Robotics Applications,” in International Conference on Field and Service Robotics (FSR), Toronto, ON, Canada, 2015.

  • [PDF] P. Nelson, W. Churchill, I. Posner, and P. Newman, “From Dusk till Dawn: Localisation at Night using Artificial Light Sources,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] C. Linegar, W. Churchill, and P. Newman, “Work Smart, Not Hard: Recalling Relevant Experiences for Vast-Scale but Time-Constrained Localisation,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] M. Gadd and P. Newman, “A Framework for Infrastructure-Free Warehouse Navigation,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015, pp. 3271-3278.

  • [PDF] P. Piniés, L. M. Paz, and P. Newman, “Dense Mono Reconstruction: Living with the Pain of the Plain Plane,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] P. Piniés, L. M. Paz, and P. Newman, “Too Much TV is Bad: Dense Reconstruction from Sparse Laser with Non-convex Regularisation,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] L. M. Paz, P. Piniés, and P. Newman, “A Variational Approach to Online Road and Path Segmentation with Monocular Vision,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] W. Churchill, C. H. Tong, C. Gurau, I. Posner, and P. Newman, “Know Your Limits: Embedding Localiser Performance Models in Teach and Repeat Maps,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] G. Pascoe, W. Maddern, A. D. Stewart, and P. Newman, “FARLAP: Fast Robust Localisation using Appearance Priors,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] W. Maddern, G. Pascoe, and P. Newman, “Leveraging Experience for Large-Scale LIDAR Localisation in Changing Cities,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] H. Grimmett, M. Buerki, L. Paz, P. Piniés, P. Furgale, I. Posner, and P. Newman, “Integrating Metric and Semantic Maps for Vision-Only Automated Parking,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] L. Berczi, I. Posner, and T. D. Barfoot, “Learning to Assess Terrain from Human Demonstration Using an Introspective Gaussian-Process Classifier,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [PDF] P. Ondruska, C. Gurau, L. Marchegiani, C. H. Tong, and I. Posner, “Scheduled Perception for Energy-Efficient Path Following,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015.

  • [DOI] D. Z. Wang, I. Posner, and P. Newman, “Model-Free Detection and Tracking of Dynamic Objects with 2D Lidar,” The International Journal of Robotics Research (IJRR), vol. 34, iss. 7, pp. 1039-1063, 2015.

  • [PDF] D. Z. Wang and I. Posner, “Voting for Voting in Online Point Cloud Object Detection,” in Proceedings of Robotics: Science and Systems, Rome, Italy, 2015.

2014

  • [PDF] C. Gurau, J. Hawke, C. H. Tong, and I. Posner, “Learning on the Job: Improving Robot Perception Through Experience,” in Neural Information Processing Systems (NIPS) Workshop on “Autonomously Learning Robots”, Montreal, Quebec, Canada, 2014.

  • [PDF] P. Ondruska and I. Posner, “The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range,” in Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS), Portsmouth, NH, USA, 2014.

  • [PDF] P. Ondruska and I. Posner, “Probabilistic Attainability Maps: Efficiently Predicting Driver-Specific Electric Vehicle Range,” in IEEE Intelligent Vehicles Symposium (IV), Dearborn, MI, USA, 2014.

  • [PDF] C. McManus, B. Upcroft, and P. Newman, “Scene Signatures: Localised and Point-less Features for Localisation,” in Proceedings of Robotics Science and Systems (RSS), Berkeley, CA, USA, 2014.

  • [PDF] W. Maddern, A. Stewart, and P. Newman, “LAPS-II: 6-DoF Day and Night Visual Localisation with Prior 3D Structure for Autonomous Road Vehicles,” in IEEE Intelligent Vehicles Symposium (IV), Dearborn, MI, USA, 2014.

  • [PDF] W. Maddern, A. Stewart, C. McManus, B. Upcroft, W. Churchill, and P. Newman, “Illumination Invariant Imaging: Applications in Robust Vision-based Localisation, Mapping and Classification for Autonomous Vehicles,” in Proceedings of the Visual Place Recognition in Changing Environments Workshop, IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.

  • [PDF] R. Paul, D. Feldman, D. Rus, and P. Newman, “Visual Precis Generation using Coresets,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.

  • [PDF] B. Upcroft, C. McManus, W. Churchill, W. Maddern, and P. Newman, “Lighting Invariant Urban Street Classification,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.

  • [PDF] C. McManus, W. Churchill, W. Maddern, A. Stewart, and P. Newman, “Shady Dealings: Robust, Long- Term Visual Localisation using Illumination Invariance,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 2014.

2013

  • [PDF] P. Furgale, U. Schwesinger, M. Rufli, W. Derendarz, H. Grimmett, P. Mühlfellner, S. Wonneberger, J. T. S. Rottmann, B. Li, B. Schmidt, T. N. Nguyen, E. Cardarelli, S. Cattani, S. Brüning, S. Horstmann, M. Stellmacher, H. Mielenz, K. Köser, M. Beermann, C. Häne, L. Heng, G. H. Lee, F. Fraundorfer, R. Iser, R. Triebel, I. Posner, P. Newman, L. Wolf, M. Pollefeys, S. Brosig, J. Effertz, C. Pradalier, and R. Siegwart, “Toward Automated Driving in Cities using Close-to-Market Sensors, an Overview of the V-Charge Project,” in IEEE Intelligent Vehicles Symposium (IV), Gold Coast, Australia, 2013, p. 809–816.

  • [PDF] R. Triebel, H. Grimmett, R. Paul, and I. Posner, “Driven Learning for Driving: How Introspection Improves Semantic Mapping,” in International Symposium on Robotics Research (ISRR), Singapore, 2013.

  • [PDF] W. Churchill and P. Newman, “Experience-based Navigation for Long-term Localisation,” The International Journal of Robotics Research (IJRR), 2013.

  • [PDF] D. Z. Wang, I. Posner, and P. Newman, “A New Approach to Model-Free Tracking with 2D Lidar,” in Proceedings of the International Symposium on Robotics Research (ISRR), Singapore, 2013.

  • [PDF] P. Corke, R. Paul, W. Churchill, and P. Newman, “Dealing with Shadows: Capturing Intrinsic Scene Appearance for Image-based Outdoor Localisation,” in Proc. of the International Conference on Intelligent Robots and Systems (IROS), 2013.

  • P. T. Furgale, P. Newman, R. Triebel, and H. G. et al, “Toward Automated Driving in Cities using Close-to-Market Sensors, an overview of the V-Charge project,” in IEEE Intelligent Vehicles Symposium, 2013.

  • [PDF] R. Triebel, H. Grimmett, R. Paul, and I. Posner, “Introspective Active Learning for Scalable Semantic Mapping,” in Workshop on Active Learning in Robotics: Exploration, Curiosity and Interaction. Robotics Science and Systems (RSS), 2013.

  • R. Triebel, H. Grimmett, and I. Posner, “Confidence Boosting: Improving the Introspectiveness of a Boosted Classifier for Efficient Learning,” in Workshop on Autonomous Learing. IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.

  • [PDF] H. Grimmett, R. Paul, R. Triebel, and I. Posner, “Knowing When We Don’t Know: Introspective Classification for Mission-Critical Decision Making,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.

  • [PDF] C. McManus, W. Churchill, A. Napier, B. Davis, and P. and Newman, “Distraction Suppression for Vision-Based Pose Estimation at City Scales,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.

  • [PDF] A. Napier, P. Corke, and P. Newman, “Cross-Calibration of Push-Broom 2D LIDARs and Cameras In Natural Scenes,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.

  • [PDF] M. Sheehan, A. Harrison, and P. Newman, “Continuous Vehicle Localisation Using Sparse 3D Sensing, Kernelised Renyi Distance and Fast Gauss Transforms,” in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2013), Tokyo, Japan, 2013.

2012

  • [PDF] R. Paul, R. Triebel, D. Rus, and P. Newman, “Semantic Categorization of Outdoor Scenes with Uncertainty Estimates using Multi-Class Gaussian Process Classification,” in Proc. of the International Conference on Intelligent Robots and Systems (IROS), Vilamoura, Portugal, 2012.

  • [PDF] W. Churchill and P. Newman, “Continually Improving Large Scale Long Term Visual Navigation of a Vehicle in Dynamic Urban Environments,” in Proc. IEEE Intelligent Transportation Systems Conference (ITSC), Anchorage, USA, 2012.

  • J. Velez, G. Hemann, A. S. Huang, I. Posner, and N. Roy, “Modelling Observation Correlations for Active Exploration and Robust Object Detection,” JAIR Journal of Artificial Intelligence Research, vol. 44, pp. 423-453, 2012.

  • [PDF] I. Baldwin and P. Newman, “Laser-only road-vehicle localization with dual 2D push-broom LIDARS and 3D priors,” in Proc.IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Vilamoura, Algarve, Portugal, 2012.

  • [PDF] B. Mathibela, M. A. Osborne, I. Posner, and P. Newman, “Can Priors Be Trusted? Learning to Anticipate Roadworks,” in Proc. IEEE Conference on Intelligent Transportation Systems (ITSC), Anchorage, AK, USA, 2012.

  • [PDF] R. Triebel, R. Paul, D. Rus, and P. Newman, “Parsing Outdoor Scenes from Streamed 3D Laser Data Using Online Clustering and Incremental Belief Updates,” in Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), Toronto, Canada, 2012.

  • [PDF] A. Napier and P. Newman, “Generation and Exploitation of Local Orthographic Imagery for Road Vehicle Localisation,” in Proc. IEEE Intelligent Vehicles Symposium (IV), Madrid, Spain, 2012.

  • [PDF] W. Churchill and P. Newman, “Practice Makes Perfect? Managing and Leveraging Visual Experiences for Lifelong Navigation,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Minnesota, USA, 2012.

  • [PDF] M. Sheehan, A. Harrison, and P. Newman, “Self-calibration for a 3D laser,” The International Journal of Robotics Research, 2012.

  • [PDF] I. Baldwin and P. Newman, “Road vehicle localization with 2D push-broom lidar and 3D priors,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Minnesota, USA, 2012.

  • [PDF] W. Maddern, A. Harrison, and P. Newman, “Lost in Translation (and Rotation): Fast Extrinsic Calibration for 2D and 3D LIDARs,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Minnesota, USA, 2012.

  • [PDF] R. Paul, D. Rus, and P. Newman, “How was your day? Online Visual Workspace Summaries using Incremental Clustering in Topic Space,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Minnesota, USA, 2012.

  • [PDF] A. Stewart and P. Newman, “LAPS – Localisation using Appearance of Prior Structure: 6-DOF Monocular Camera Localisation using Prior Pointclouds,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Minnesota, USA, 2012.

  • [PDF] D. Z. Wang, I. Posner, and P. Newman, “What Could Move? Finding Cars, Pedestrians and Bicyclists in 3D Laser Data,” in Proc. IEEE International Conference on Robotics and Automation (ICRA), Minnesota, USA, 2012.

2011

  • [PDF] A. Harrison and P. Newman, “TICSync: Knowing When Things Happened,” in Proc. IEEE International Conference on Robotics and Automation (ICRA2011), Shanghai, China, 2011.

  • [PDF] J. Velez, G. Hemann, A. S. Huang, I. Posner, and N. Roy, “Active Exploration for Robust Object Detection,” in International Joint Conference on Artificial Intelligence (IJCAI), Barcelona, Spain, 2011.

  • [PDF] J. Velez, G. Hemann, A. S. Huang, I. Posner, and N. Roy, “Planning to Perceive: Exploiting Mobility For Robust Object Detection,” in International Conference on Automated Planning and Scheduling, Freiburg, Germany, 2011.

  • [PDF] C. Mei, E. Sommerlade, G. Sibley, P. Newman, and I. Reid, “Hidden View Synthesis using Real-Time Visual SLAM for Simplifying Video Surveillance Analysis,” in Proc. IEEE International Conference on Robotics and Automation (ICRA2011), Shanghai, China, 2011.

  • [PDF] M. Smith, I. Posner, and P. Newman, “Adaptive compression for 3D laser data,” The International Journal of Robotics Research, vol. 30, iss. 7, pp. 914-935, 2011.

  • [PDF] L. Murphy and P. Newman, “Risky Planning: Path Planning over Costmaps with a Probabilistically Bounded Speed-Accuracy Tradeoff,” in Proc. IEEE International Conference on Robotics and Automation (ICRA2011), Shanghai, China, 2011.

  • [PDF] R. Paul and P. Newman, “Self Help: Seeking Out Perplexing Images for Ever Improving Navigation,” in Proc. IEEE International Conference on Robotics and Automation (ICRA2011), Shanghai, China, 2011.

  • [PDF] R. Shade and P. Newman, “Choosing Where To Go: Complete 3D Exploration With Stereo,” in Proc. IEEE International Conference on Robotics and Automation (ICRA2011), Shanghai, China, 2011.

2010

  • [PDF] A. Napier, G. Sibley, and P. Newman, “Real-Time Bounded-Error Pose Estimation for Road Vehicles Using Vision,” in 13th Intl. IEEE Conference on Intelligent Transportation Systems (ITSC), Funchal, Portugal, 2010, p. pp. 1141–1146.

  • [PDF] I. Baldwin and P. Newman, “Non-parametric Learning for Natural Plan Generation,” in International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 2010.

  • [PDF] I. Baldwin and P. Newman, “Teaching a Randomized Planner to plan with Semantic fields,” in Towards Autonomous Robotic Systems, Plymouth, UK, 2010.

  • [PDF] M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, “Nested autonomy for unmanned marine vehicles with MOOS-IvP,” J. Field Robotics, pp. 834-875, 2010.

  • [PDF] C. Mei, G. Sibley, and P. Newman, “Closing Loops Without Places,” in International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 2010.

  • [PDF] C. Mei, G. Sibley, M. Cummins, P. Newman, and I. Reid, “RSLAM: A System for Large-Scale Mapping in Constant-Time using Stereo,” International Journal of Computer Vision, pp. 1-17, 2010.

  • [PDF] M. Cummins and P. Newman, “Appearance-only SLAM at Large Scale with FAB-MAP 2.0,” The International Journal of Robotics Research, 2010.

  • [PDF] M. Cummins and P. Newman, “Accelerating FAB-MAP with Concentration Inequalities,” IEEE Transactions on Robotics, vol. 26, iss. 6, 2010.

  • [PDF] J. Frost, A. Harrison, S. Pulman, and P. Newman, “A Probabilistic Approach to Modelling Spatial Language with Its Application To Sensor Models,” in Proc. of the Workshop on Computational Spatial Language Interpretation at International Conference on Spatial Cognition, Portland, Oregon, 2010.

  • [PDF] G. Sibley, C. Mei, I. Reid, and P. Newman, “Vast Scale Outdoor Navigation Using Adaptive Relative Bundle Adjustment,” International Journal of Robotics Research, vol. 29, iss. 8, pp. 958-980, 2010.

  • [PDF] I. Posner, P. Corke, and P. Newman, “Using Text-Spotting to Query the World,” in Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2010.

  • [PDF] M. Smith, I. Posner, and P. Newman, “Generating Implicit Surfaces from Lidar Data,” in Towards Autonomous Robotic Systems, Plymouth, UK, 2010.

  • [PDF] L. Murphy and P. Newman, “Planning Most-Likely Paths from Overhead Imagery,” in Proc. IEEE International Conference on Robotics and Automation (ICRA’10), Anchorage, AK, 2010.

  • [PDF] R. Paul and P. Newman, “FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance,” in Proc. IEEE International Conference on Robotics and Automation (ICRA’10), Anchorage, Alaska, 2010, pp. 2649-2656.

  • [PDF] R. Shade and P. Newman, “Discovering and Mapping Complete Surfaces With Stereo,” in Proc. IEEE International Conference on Robotics and Automation (ICRA’10), Anchorage, Alaska, 2010, pp. 3910-3915.

  • [PDF] M. Sheehan, A. Harrison, and P. Newman, “Automatic Self-Calibration Of A Full Field-Of-View 3D n-Laser Scanner,” in In Proceedings of the International Symposium on Experimental Robotics (ISER2010), New Delhi and Agra, India, 2010.

  • [PDF] G. Sibley, C. Mei, I. Reid, and P. Newman, “Planes, Trains and Automobiles ñ Autonomy for the Modern Robot,” in In Proceedings of the IEEE International Conference on Robotics and Automation, Anchorage, Alaska, USA, 2010, pp. 285-292.

  • [PDF] M. Smith, I. Posner, and P. Newman, “Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data,” in Proceedings of Robotics: Science and Systems VI, Zaragoza, Spain, 2010.

2009

  • [PDF] M. Cummins and Paul Newman, “Highly Scalable Appearance-Only SLAM ñ FAB-MAP 2.0,” in Robotics Science and Systems (RSS), Seattle, USA, 2009.

  • [PDF] A. Harrison and P. Newman, “Image and Sparse Laser Fusion for Dense Scene Reconstruction,” in Proceedings of the 7th International Conference on Field and Service Robotics, Cambridge, Massachusetts, 2009.

  • [PDF] C. Mei, G. Sibley, M. Cummins, P. Newman, and I. Reid, “A Constant Time Efficient Stereo SLAM System,” in Proceedings of the British Machine Vision Conference (BMVC), London, 2009.

  • P. Newman, G. Sibley, M. Cummins, M. Smith, A. Harrison, C. Mei, and I. Reid, “Toward Life Long Mapping,” in Proc. of the Int. Symposium of Robotics Research (ISRR), Lucerne, Switzerland, 2009.

  • [PDF] [DOI] P. Newman, G. Sibley, M. Smith, M. Cummins, A. Harrison, C. Mei, I. Posner, R. Shade, D. Schroeter, L. Murphy, W. Churchill, D. Cole, and I. Reid, “Navigating, Recognising and Describing Urban Spaces With Vision and Laser,” The International Journal of Robotics Research, vol. 28, 2009.

  • [PDF] [DOI] I. Posner, M. Cummins, and P. Newman, “A generative framework for fast urban labeling using spatial and temporal context,” Autonomous Robots, vol. 26, iss. 2-3, pp. 153-170, 2009.

  • [PDF] G. Sibley, C. Mei, I. Reid, and P. Newman, “Adaptive Relative Bundle Adjustment,” in Robotics Science and Systems Conference, Seattle, USA, 2009.

  • [PDF] [DOI] M. Smith, I. Baldwin, W. Churchill, R. Paul, and P. Newman, “The New College Vision and Laser Data Set,” The International Journal of Robotics Research, vol. 28, iss. 5, pp. 595-599, 2009.

2008

  • [PDF] M. Cummins and P. Newman, “Accelerated Appearance-Only SLAM,” in Proc. IEEE International Conference on Robotics and Automation(ICRA’08), Pasadena, California, 2008.

  • [PDF] [DOI] M. Cummins and P. Newman, “FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance,” The International Journal of Robotics Research, vol. 27, iss. 6, pp. 647-665, 2008.

  • [PDF] A. Harrison and P. Newman, “High Quality 3D Laser Ranging Under General Vehicle Motion,” in Proc. IEEE International Conference on Robotics and Automation (ICRA’08), Pasadena, California, 2008.

  • [PDF] L. Murphy and P. Newman, “Using Incomplete Online Metric Maps for Topological Exploration with the Gap Navigation Tree,” in Proc. IEEE International Conference on Robotics and Automation (ICRA’08), Pasadena,California, 2008.

  • [PDF] I. Posner, M. Cummins, and P. Newman, “Fast Probabilistic Labeling of City Maps,” in Proceedings of Robotics: Science and Systems IV, Zurich, Switzerland, 2008.

  • [PDF] [DOI] I. Posner, D. Schroeter, and P. Newman, “Online generation of scene descriptions in urban environments,” Robotics and Autonomous Systems, vol. 56, iss. 11, pp. 901-914, 2008.

  • [PDF] I. Posner, D. Schroeter, and P. Newman, “Using Scene Similarity for Place Labelling,” in Springer Tracts in Advanced Robotics, Berlin / Heidelberg: Springer, 2008, vol. 39, pp. 85-98.

  • [PDF] D. Schroeter and P. Newman, “On the Robustness of Visual Homing under Landmark Uncertainty,” in In Proc. of 10th International Conference on Autonomous Systems (IAS), Baden Baden, Germany, 2008.

  • [PDF] B. Williams, M. Cummins, J. Neira, P. Newman, I. Reid, and J. D. Tardos, “An image-to-map loop closing method for monocular SLAM,” in Proc. International Conference on Intelligent Robots and and Systems, Nice, France, 2008.

2007

  • [PDF] K. L. Ho and P. Newman, “Detecting Loop Closure with Scene Sequences,” International Journal of Computer Vision, vol. 74, iss. 3, pp. 261-286, 2007.

  • [PDF] M. Chandran-Ramesh and P. Newman, “Assessing Map Quality using Conditional Random Fields,” in Proc. of the International Conference on Field and Service Robotics, Chamonix Mont-Blanc, France, 2007.

  • [PDF] M. Chandran-Ramesh and P. Newman, “Assessing Map Quality and Error Causations using Conditional Random Fields,” in Proceedings of the 6th. IFAC Symposium Intelligent Autonomous Vehicles (IAV), Toulouse, France, 2007.

  • [PDF] D. Cole and P. Newman, “Context and Feature Sensitive Re-sampling from Discrete Surface Measurements,” in Proceedings of Robotics: Science and Systems, Atlanta, GA, USA, 2007.

  • [PDF] M. Cummins and P. Newman, “Probabilistic Appearance Based Navigation and Loop Closing,” in Proc. IEEE International Conference on Robotics and Automation(ICRA’07), Rome, 2007.

  • [PDF] P. Newman, M. Chandran-Ramesh, D. Cole, M. Cummins, A. Harrison, I. Posner, and D. Schroeter, “Describing, Navigating and Recognising Urban Spaces – Building An End-to-End SLAM System,” in Proc. of the Int. Symposium of Robotics Research (ISRR), Hiroshima,Japan, 2007.

  • [PDF] I. Posner, D. Schroeter, and P. Newman, “Describing Composite Urban Workspaces,” in Proc. of the Int. Conference on Robotics and Automation, Rome, 2007.

2006

  • [PDF] M. Benjamin, J. Curcio, J. Leonard, and P. Newman, “Protocol-Based COLREGS Collision Avoidance Navigation Between Unmanned Marine Surface Craft,” Journal of Field Robotics, vol. 23, iss. 5, pp. 333-346, 2006.

  • [PDF] M. Benjamin, J. Curcio, J. Leonard, and P. Newman, “Navigation of Unmanned Marine Vehicles in Accordance with the Rules of the Road.,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Orlando Florida USA, 2006.

  • [PDF] M. Benjamin, M. Grund, and P. Newman, “Multi-Objective Optimization of Sensor Quality with Efficient Marine Vehicle Task Execution,” in International Conference on Robotics and Automation, Orlando, Florida, 2006.

  • [PDF] M. Chandran and P. Newman, “Motion Estimation from Map Quality with Millimeter Wave Radar,” in Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006.

  • [PDF] D. Cole and P. Newman, “Using Laser Range Data for 3D SLAM in Outdoor Environments,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Orlando Florida USA, 2006.

  • [PDF] K. L. Ho and P. Newman, “Loop Closure Detection in SLAM by Combining Visual and Spatial Appearance,” Robotics and Autonomous Systems, vol. 54, p. 740–749, 2006.

  • [PDF] P. Newman, D. Cole, and K. L. Ho, “Outdoor SLAM using Visual Appearance and Laser Ranging,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Orlando Florida USA, 2006.

  • [PDF] I. Posner, D. Schroeter, and P. Newman, “Using Scene Similarity for Place Labelling,” in Proc. of the Int. Symposium on Experimental Robotics, Rio, 2006.

2005

  • [PDF] D. Cole, A. Harrison, and P. Newman, “Using Naturally Salient Regions for SLAM with 3D Laser Data,” in International Conference on Robotics and Automation, Barcelona, Spain, 2005.

  • [PDF] S. Dobnik, S. Pulman, P. Newman, and A. Harrison, “Teaching a Robot Spatial Expressions,” in Second ACL-SIGSEM, Colchester, UK, 2005.

  • [PDF] K. L. Ho and P. Newman, “Multiple Map Intersection Detection using Visual Appearance,” in 3rd International Conference on Computational Intelligence, Robotics and Autonomous Systems, Singapore, 2005.

  • [PDF] K. L. Ho and P. Newman, “Combining Visual and Spatial Appearance for Loop Closure Detection in SLAM,” in 2nd European Conference on Mobile Robots ECMR, Ancona, Italy, 2005.

  • [PDF] P. Newman and K. L. Ho, “SLAM – Loop Closing with Visually Salient Features,” in IEEE International Conference on Robotics and Automation, 2005.

2004

  • [PDF] M. Bosse, P. M. Newman, J. J. Leonard, and S. Teller, “SLAM in Large-scale Cyclic Environments using the Atlas Framework.,” The International Journal of Robotics Research, vol. 23, iss. 12, pp. 1113-1139, 2004.

  • [PDF] R. J. Rikoski, J. J. Leonard, Paul Newman, and H. Schmidt, “Trajectory Sonar Perception in the Ligurian Sea,” in Experimental Robotics IX: Proceedings of the International Symposium of Robotics Research, Singapore, 2004.

2003

  • [PDF] M. Bosse, P. Newman, J. Leonard, M. Soika, W. Feiten, and S. Teller, “An Atlas Framework for Scalable Mapping,” in Proceedings of the IEEE International Conference on Robotics and Automation, Taiwan, 2003.

  • [PDF] P. Newman and J. J. Leonard, “Pure range-only subsea SLAM.,” in Proceedings of the IEEE International Conference on Robotics and Automation, Taiwan, 2003.

  • [PDF] P. Newman, J. J. Leonard, and R. R. Rikoski, “Towards Constant-Time SLAM on an Autonomous Underwater Vehicle Using Synthetic Aperture Sonar.,” in Proceedings of the International Symposium of Robotics Research, Sienna, 2003.

  • [PDF] P. M. Newman, M. Bosse, and J. J. Leonard, “Autonomous Feature-based Exploration.,” in IEEE International Conference on Robotics and Automation, Taiwan, 2003.

  • [PDF] P. M. Newman and J. J. Leonard, “Consistent Convergent Constant Time SLAM.,” in Proceedings of the International Joint Conference on Artificial Intelligence, Acapulco, Mexico, 2003.

2002

  • [PDF] J. Leonard, R. Rikoski, P. Newman, and M. Bosse, “Mapping Partially Observable Features from Multiple Uncertain Vantage Points.,” The International Journal of Robotics Research, vol. 21, iss. 10, pp. 943-975, 2002.

  • [PDF] P. Newman, J. J. Leonard, J. Neira, and J. TardÛs, “Explore and Return: Experimental Validation of Real Time Concurrent Mapping and Localization.,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington, USA, 2002, pp. 1802-1809.

  • [PDF] R. J. Rikoski, J. J. Leonard, and P. Newman, “Stochastic Mapping Frameworks,” in Proceedings of the IEEE International Conference on Robotics and Automation, Washington, USA, 2002, pp. 426-433.

  • [PDF] M. Stojanovic, L. Freitag, J. Leonard, and P. Newman, “A network protocol for Multiple AUV Localization,” in Proceedings of the MTS/IEEE Oceans 2002 Conference, Biloxi, USA, 2002, pp. 604-611.

  • [PDF] J. TardÛs, J. Neira, P. Newman, and J. J. Leonard, “Robust Mapping and Localization in Indoor Environments using Sonar Data,” The International Journal of Robotics Research, vol. 21, iss. 4, pp. 311-330, 2002.

2001

  • [PDF] M. W. M. G. Dissanayake, P. M. Newman, H. F. Durrant-Whyte, S. Clark, and M. Csorba., “A solution to the simultaneous localization and map building (SLAM) problem,” IEEE Transactions on Robotics and Automation, vol. 17, iss. 3, pp. 229-241, 2001.

  • [PDF] S. B. Williams, P. Newman, J. Rosenblatt, G. Dissanayake, and H. F. Durrant-Whyte, “Autonomous Underwater Navigation and Control,” Robotica, vol. 19, iss. 5, pp. 481-496, 2001.

2000

  • M. W. M. G. Dissanayake, P. Newman, H. F. Durrant-Whyte, S. Clark, and M. Csorba, “An Experimental and Theoretical Investigation into Simultaneous Localisation and Map Building,” in The Sixth International Symposium on Experimental Robotics VI, Sydney, Australia, 2000, p. 265–274.

  • [PDF] S. B. Williams, P. Newman, M. W. M. G. Dissanayake, and H. F. and Durrant-Whyte, “Autonomous underwater simultaneous localisation and map building,” in IEEE International Conference on Robotics and Automation, San Francisco, USA, 2000.

  • [PDF] S. B. Williams, P. Newman, M. W. M. G. Dissanayake, J. Rosenblatt, and H. F. Durrant-Whyte, “A decoupled, distributed AUV control architecture,” , vol. 1, pp. 246-251, 2000.

1999

  • [PDF] S. B. Williams, P. Newman, S. Majumder, J. Rosenblatt, and H. F. Durrant-Whyte, “Autonomous transect surveying of the Great Barrier Reef,” in Proceedings of the Australian Conference on Robotics and Automation (ACRA ’99), Brisbane, Australia, 1999, pp. 16-20.

1997

  • P. Newman and H. F. Durrant-Whyte, “Towards Terrain Aided Navigation of a Subsea Vehicle,” in Proceedings of the International Conference on Field and Service Robotics (FSR), Canberra, Australia, 1997, pp. 244-248.