5 papers
COOPERA: Continual Open-Ended Human-Robot Assistance
Chenyang Ma, Kai Lu, Ruta Desai +3
To understand and collaborate with humans, robots must account for individual human traits, habits, and activities over time. However, most robotic assistants lack these abilities,…
Grounding Multimodal LLMs to Embodied Agents that Ask for Help with Reinforcement Learning
Ram Ramrakhya, Matthew Chang, Xavier Puig +3
Embodied agents operating in household environments must interpret ambiguous and under-specified human instructions. A capable household robot should recognize ambiguity and ask re…
RobotMover: Learning to Move Large Objects From Human Demonstrations
Tianyu Li, Joanne Truong, Jimmy Yang +4
Moving large objects, such as furniture or appliances, is a critical capability for robots operating in human environments. This task presents unique challenges, including whole-bo…
ADAPT: Actively Discovering and Adapting to Preferences for any Task
Maithili Patel, Xavier Puig, Ruta Desai +4
Assistive agents should be able to perform under-specified long-horizon tasks while respecting user preferences. We introduce Actively Discovering and Adapting to Preferences for a…
PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks
Matthew Chang, Gunjan Chhablani, Alexander Clegg +17
We present a benchmark for Planning And Reasoning Tasks in humaN-Robot collaboration (PARTNR) designed to study human-robot coordination in household activities. PARTNR tasks exhib…