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20172023
most citedHow to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned

565 citations · 668 across the 20 of their papers we have counts for

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29 papers · 1 filter

cs.RO2023

Discovering Adaptable Symbolic Algorithms from Scratch

Stephen Kelly, Daniel S. Park, Xingyou Song +8

Autonomous robots deployed in the real world will need control policies that rapidly adapt to environmental changes. To this end, we propose AutoRobotics-Zero (ARZ), a method based…

cs.RO2023

Transforming a Quadruped into a Guide Robot for the Visually Impaired: Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism

J. Taery Kim, Wenhao Yu, Yash Kothari +3

This paper explores the principles for transforming a quadrupedal robot into a guide robot for individuals with visual impairments. A guide robot has great potential to resolve the…

cs.RO2023

Language to Rewards for Robotic Skill Synthesis

Wenhao Yu, Nimrod Gileadi, Chuyuan Fu +17

Large language models (LLMs) have demonstrated exciting progress in acquiring diverse new capabilities through in-context learning, ranging from logical reasoning to code-writing.…

cs.RO2023

CAJun: Continuous Adaptive Jumping using a Learned Centroidal Controller

Yuxiang Yang, Guanya Shi, Xiangyun Meng +4

We present CAJun, a novel hierarchical learning and control framework that enables legged robots to jump continuously with adaptive jumping distances. CAJun consists of a high-leve…

cs.RO2023

SayTap: Language to Quadrupedal Locomotion

Yujin Tang, Wenhao Yu, Jie Tan +3

Large language models (LLMs) have demonstrated the potential to perform high-level planning. Yet, it remains a challenge for LLMs to comprehend low-level commands, such as joint an…

cs.RO202313 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…