5 papers
Jointly Learning Predicates and Actions Enables Zero-Shot Skill Composition
Benedict Quartey, Sebastian Castro, Eric Rosen +3
Learning from Demonstration (LfD) enables robots to learn complex behaviors from expert examples, yet existing approaches often fail to generalize to new compositions of known skil…
λ: A Benchmark for Data-Efficiency in Long-Horizon Indoor Mobile Manipulation Robotics
Ahmed Jaafar, Shreyas Sundara Raman, Sudarshan Harithas +7
Learning to execute long-horizon mobile manipulation tasks is crucial for advancing robotics in household and workplace settings. However, current approaches are typically data-ine…
Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody
David Sasu, Kweku Andoh Yamoah, Benedict Quartey +1
Enabling robots to accurately interpret and execute spoken language instructions is essential for effective human-robot collaboration. Traditional methods rely on speech recognitio…
Verifiably Following Complex Robot Instructions with Foundation Models
Benedict Quartey, Eric Rosen, Stefanie Tellex +1
When instructing robots, users want to flexibly express constraints, refer to arbitrary landmarks, and verify robot behavior, while robots must disambiguate instructions into speci…
Bootstrapping Object-level Planning with Large Language Models
David Paulius, Alejandro Agostini, Benedict Quartey +1
We introduce a new method that extracts knowledge from a large language model (LLM) to produce object-level plans, which describe high-level changes to object state, and uses them…