Biography
Nick is an Associate Professor in Engineering Science (Robotics) and a Tutorial Fellow in Engineering Science at Pembroke College. He joined the Oxford Robotics Institute in September 2017. Previously he was a Reader in Autonomous Intelligent Robotics in the School of Computer Science at the University of Birmingham, where he also completed a BSc and PhD in Artificial Intelligence. For more information see: http://nickhaw.es
Most Recent Publications
Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots
Chiou M, Hawes N & Stolkin R (2021), ACM Transactions on Human-Robot Interaction, 10(4)
Simulating ionising radiation in gazebo for robotic nuclear inspection challenges
Wright T, West A, Licata M, Hawes N & Lennox B (2021), Robotics, 10(3)
Online plan modification in uncertain resource-constrained environments
Harris CA, Hawes N & Dearden R (2021), Robotics and Autonomous Systems, 140
Minimax regret optimisation for robust planning in uncertain Markov decision processes
Rigter M, Lacerda B & Hawes N (2021), Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11930-11938
Long-run multi-robot planning under uncertain action durations for persistent tasks
Azevedo C, Lacerda B, Hawes N & Lima P (2021), Proceedings of the IEEE International Workshop on Intelligent Robots and Systems (IROS), 4323-4328
Research
Nick’s research interests lie in the application of Artificial Intelligence (AI) techniques to create intelligent, autonomous robots that can work with or for humans. He has worked on long-term autonomy for mobile robots; mixed initiative or shared autonomy between humans and robots; information-processing architectures for intelligent systems; the integration of AI planning techniques into a variety of robot systems; and the use of qualitative semantic and spatial representations to enable robots to reason about the possibilities for action in their worlds.
From 2013 to 2017 Nick was the coordinator of the STRANDS project (Spatio-Temporal Representations and Activities for Cognitive Control in Long-Term Scenarios), a 4-year EU FP7 Integrating Project. Please see the project’s website, the STRANDS overview paper, or the “Success Stories of FP7” presentation at the European Robotics Forum 2017.
Nick has given invited talks to many conferences, workshops, summer schools. Follow the links to watch Nick’s talk on learning and semantic representations to the 2016 WASP graduate school, and a tutorial on probabilistic planning for mobile robots at the 4th Lucia School on AI and Robotics.
Most Recent Publications
Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots
Chiou M, Hawes N & Stolkin R (2021), ACM Transactions on Human-Robot Interaction, 10(4)
Simulating ionising radiation in gazebo for robotic nuclear inspection challenges
Wright T, West A, Licata M, Hawes N & Lennox B (2021), Robotics, 10(3)
Online plan modification in uncertain resource-constrained environments
Harris CA, Hawes N & Dearden R (2021), Robotics and Autonomous Systems, 140
Minimax regret optimisation for robust planning in uncertain Markov decision processes
Rigter M, Lacerda B & Hawes N (2021), Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11930-11938
Long-run multi-robot planning under uncertain action durations for persistent tasks
Azevedo C, Lacerda B, Hawes N & Lima P (2021), Proceedings of the IEEE International Workshop on Intelligent Robots and Systems (IROS), 4323-4328
Publications
See Nick’s personal website or Google Scholar profile.
Most Recent Publications
Mixed-initiative Variable Autonomy for Remotely Operated Mobile Robots
Chiou M, Hawes N & Stolkin R (2021), ACM Transactions on Human-Robot Interaction, 10(4)
Simulating ionising radiation in gazebo for robotic nuclear inspection challenges
Wright T, West A, Licata M, Hawes N & Lennox B (2021), Robotics, 10(3)
Online plan modification in uncertain resource-constrained environments
Harris CA, Hawes N & Dearden R (2021), Robotics and Autonomous Systems, 140
Minimax regret optimisation for robust planning in uncertain Markov decision processes
Rigter M, Lacerda B & Hawes N (2021), Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11930-11938
Long-run multi-robot planning under uncertain action durations for persistent tasks
Azevedo C, Lacerda B, Hawes N & Lima P (2021), Proceedings of the IEEE International Workshop on Intelligent Robots and Systems (IROS), 4323-4328
