Planning for Multiple Robots in Congested Environments When most of us plan journeys, chances are at some point we open Google Maps to find an array of colours telling us that we will probably experience traffic at certain points on our journey. This allows us to plan our [...]
Learning from demonstration and reinforcement learning have been applied to many difficult problems in sequential decision making and control. In most settings, it is assumed that the demonstrations available are fixed. In this work, we consider learning from demonstration in the context of shared autonomy...
Paul joined ORI in October 2019 and works with Nick Hawes
Mohamed joined ORI in 2019 and is supervised by Nick Hawes.
Anna joined ORI in 2019 and is supervised by Nick Hawes.
Betty is a mobile service robot from the Oxford Robotics Institute. She has been extensively used the GOALS group to demonstrate long-term autonomous behaviour in real-world dynamic environments. Her software was originally developed by a European consortium as part of the STRANDS Project. In that project Betty and [...]
Charlie joined ORI in 2018 and is supervised by Nick Hawes.
Marc joined ORI in 2018 and is supervised by Nick Hawes.
Michael joined ORI in 2018 and is supervised by Nick Hawes.
Consider an office robot that must execute a range of tasks such as guiding visitors to offices; checking whether fire exits are clear; carrying and delivering items as requested by office users; and making announcements (“staff meeting in 10 minutes!”). A crucial requirement for such a robot [...]