2 citations · 3 across the 9 of their papers we have counts for
9 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…
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…
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…
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…
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…
Exploiting Contextual Structure to Generate Useful Auxiliary Tasks
Benedict Quartey, Ankit Shah, George Konidaris
Reinforcement learning requires interaction with an environment, which is expensive for robots. This constraint necessitates approaches that work with limited environmental interac…