MRG Highlights

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LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic

LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic This paper presents a system for improving the robustness of LiDAR lateral localisation systems. This is made possible by including detections of road boundaries which are invisible to the sensor (due to occlusion, e.g. traffic) but can be located by our Occluded Road Boundary Inference Deep [...]

LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic2020-03-10T17:57:34+00:00

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance Abstract - This paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave radar - a commercially promising sensor poised for exploitation in mobile autonomy. We show how a rotationally-invariant metric embedding for radar scans can [...]

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance2020-03-10T17:54:45+00:00

Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset

Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset Abstract - We describe the release of reference data towards a challenging long-term localisation and mapping benchmark based on the large-scale Oxford RobotCar Dataset. The release includes 72 traversals of a route through Oxford, UK, gathered in all illumination, weather and traffic conditions, and is [...]

Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset2020-02-25T10:31:16+00:00

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning Abstract - This paper presents a system for robust, large-scale topological localisation using Frequency-Modulated ContinuousWave (FMCW) scanning radar. We learn a metric space for embedding polar radar scans using CNN and NetVLAD architectures traditionally applied to the visual domain. However, we tailor the feature extraction [...]

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning2020-01-30T12:33:15+00:00

I Can See Clearly Now : Image Restoration via De-Raining

This blog post provides an overview of our paper: [bibtex key="ICRA19_porav"] Abstract We present a method for improving segmentation tasks on images affected by adherent rain drops and streaks. We introduce a novel stereo dataset recorded using a system that allows one lens to be affected by real water droplets while keeping the other lens [...]

I Can See Clearly Now : Image Restoration via De-Raining2019-11-22T12:22:23+00:00

A Weather-proof Vehicle for Long-term Autonomy in Outdoor Environments

Our new all-weather platform pictured outside Blenheim Palace. For more information please take a look at the paper as well as the presentation. This blog post provides an overview of our paper which was recently presented by Stephen Kyberd at the 12th Conference on Field and Service Robotics, Tokyo, Japan – “The Hulk: [...]

A Weather-proof Vehicle for Long-term Autonomy in Outdoor Environments2019-12-15T12:12:02+00:00

Introspective Radar Odometry

How do we know when we don’t know? This is an important question to answer in any situation where we need to navigate through our surroundings, and something any autonomous mobile robot needs to know too. We discuss this introspection capability and its importance to our radar-based navigation algorithms [...]

Introspective Radar Odometry2019-11-21T09:56:10+00:00

The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping

Accurate scene understanding is paramount to the deployment of autonomous vehicles in real-world traffic. They need to perceive and fully understand their environment to accomplish their navigation tasks in a natural and safe manner. To accomplish this, we have recently introduced a hierarchical framework to describe [...]

The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping2019-06-24T14:22:58+01:00

Fast Radar Motion Estimation

Fast Radar Motion Estimation This blog post provides an overview of our paper “Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision” by Roberto Aldera, Daniele De Martini, Matthew Gadd, and Paul Newman which was recently accepted for publication at the IEEE International Conference on [...]

Fast Radar Motion Estimation2019-11-21T09:54:57+00:00

Radar-only ego-motion estimation in difficult settings via graph matching

Radar-only ego-motion estimation in difficult settings via graph matching Abstract - Radar detects stable, long-range objects under variable weather and lighting conditions, making it a reliable and versatile sensor well suited for ego-motion estimation. In this work, we propose a radar-only odometry pipeline that is highly robust to radar artifacts (e.g., speckle noise and [...]

Radar-only ego-motion estimation in difficult settings via graph matching2020-02-12T13:51:12+00:00