most citedDo As I Can, Not As I Say: Grounding Language in Robotic Affordances

524 citations · 748 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2023★ 13 cited

Barkour: Benchmarking Animal-level Agility with Quadruped Robots

Ken Caluwaerts, Atil Iscen, J. Chase Kew +41

Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biol…

cs.RO2023

Learning and Adapting Agile Locomotion Skills by Transferring Experience

Laura Smith, J. Chase Kew, Tianyu Li +5

Legged robots have enormous potential in their range of capabilities, from navigating unstructured terrains to high-speed running. However, designing robust controllers for highly…

cs.RO2022★ 208 cited

Inner Monologue: Embodied Reasoning through Planning with Language Models

Wenlong Huang, Fei Xia, Ted Xiao +14

Recent works have shown how the reasoning capabilities of Large Language Models (LLMs) can be applied to domains beyond natural language processing, such as planning and interactio…

cs.RO2022★ 524 cited

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Michael Ahn, Anthony Brohan, Noah Brown +42

Large language models can encode a wealth of semantic knowledge about the world. Such knowledge could be extremely useful to robots aiming to act upon high-level, temporally extend…

cs.RO2022★ 3 cited

Safe Reinforcement Learning for Legged Locomotion

Tsung-Yen Yang, Tingnan Zhang, Linda Luu +3

Designing control policies for legged locomotion is complex due to the under-actuated and non-continuous robot dynamics. Model-free reinforcement learning provides promising tools…