Goal-Oriented Long-Lived Systems
The Goal-Oriented Long-Lived Systems (GOALS) Lab performs research around the problems of behaviour generation for autonomous systems. In particular we focus on long-term autonomy and task and mission planning for mobile robots which must operate for extended periods (days, weeks or months) in dynamic, uncertain environments. To create long-term autonomous behaviour we explore the application of artificial intelligence techniques to robots, particularly planning under uncertainty and machine learning, such that the longer robots act in an environment, the better they perform.
RT @hawesie: Sunday is @GOALS_oxford day at #AAAI23. If you’re interested in planning under uncertainty, chance-constrained resource allo…
You can find out more about the paper here: https://t.co/PAFs0snEx6
The framework is evaluated by planning for robot missions in a hazardous nuclear environment (with unknown radiation levels) and a challenging underwater setting (with unknown currents).
If you're at @corl_conf #CoRL2022 and interested in planning under uncertainty for robot missions, make sure to visit @m_budd's poster on Saturday morning! His work uses GPs as part of a Bayes-optimal framework for planning single missions in partially-known environments. https://t.co/X2eoRMrkj0
RT @dynamicrobots: Bravo to Ioannis and robotics researchers around the world #KianPirfalak
RT @MauriceFallon: Reminder: funded position - deadline approaching. Join my group working on mobile robot navigation. I particularly welc…
RT @mmattamala: Really nice work on reactive control by @GOALS_oxford colleagues @lbrudermueller and @hawesie !
RT @hawesie: I’m very pleased to see some @oxfordrobots (@dynamicrobots @GOALS_oxford) work in here. Spot is an awesome platform for robust…
RT @UniofOxford: PHOTOS: @oxfordrobots at Blenheim Palace 🤖 The Boston Dynamics Spot is being used at the palace to gather data about spec…