activity
20142023
most citedLearning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

166 citations · 299 across the 10 of their papers we have counts for

collaborators

12 papers

cs.RO2023★ 166 cited

Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning

Tuomas Haarnoja, Ben Moran, Guy Lever +25

We investigate whether Deep Reinforcement Learning (Deep RL) is able to synthesize sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be compo…

cs.LG2022★ 1 cited

SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration

Giulia Vezzani, Dhruva Tirumala, Markus Wulfmeier +13

The ability to effectively reuse prior knowledge is a key requirement when building general and flexible Reinforcement Learning (RL) agents. Skill reuse is one of the most common a…

cs.RO2022★ 1 cited

NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields

Arunkumar Byravan, Jan Humplik, Leonard Hasenclever +8

We present a system for applying sim2real approaches to "in the wild" scenes with realistic visuals, and to policies which rely on active perception using RGB cameras. Given a shor…

cs.RO2022★ 20 cited

Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors

Steven Bohez, Saran Tunyasuvunakool, Philemon Brakel +18

We investigate the use of prior knowledge of human and animal movement to learn reusable locomotion skills for real legged robots. Our approach builds upon previous work on imitati…

cs.LG2021★ 2 cited

Learning Transferable Motor Skills with Hierarchical Latent Mixture Policies

Dushyant Rao, Fereshteh Sadeghi, Leonard Hasenclever +8

For robots operating in the real world, it is desirable to learn reusable behaviours that can effectively be transferred and adapted to numerous tasks and scenarios. We propose an…

cs.RO2019★ 45 cited

MuSHR: A Low-Cost, Open-Source Robotic Racecar for Education and Research

Siddhartha S. Srinivasa, Patrick Lancaster, Johan Michalove +8

We present MuSHR, the Multi-agent System for non-Holonomic Racing. MuSHR is a low-cost, open-source robotic racecar platform for education and research, developed by the Personal R…