1 citations · 1 across the 9 of their papers we have counts for
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GeCCo -- a Generalist Contact-Conditioned Policy for Loco-Manipulation Skills on Legged Robots
Vassil Atanassov, Wanming Yu, Siddhant Gangapurwala +2
Most modern approaches to quadruped locomotion focus on using Deep Reinforcement Learning (DRL) to learn policies from scratch, in an end-to-end manner. Such methods often fail to…
Acrobotics: A Generalist Approach to Quadrupedal Robots' Parkour
Guillaume Gagné-Labelle, Vassil Atanassov, Ioannis Havoutis
Climbing, crouching, bridging gaps, and walking up stairs are just a few of the advantages that quadruped robots have over wheeled robots, making them more suitable for navigating…
Improving Trajectory Stitching with Flow Models
Reece O'Mahoney, Wanming Yu, Ioannis Havoutis
Generative models have shown great promise as trajectory planners, given their affinity to modeling complex distributions and guidable inference process. Previous works have succes…
Reference Free Platform Adaptive Locomotion for Quadrupedal Robots using a Dynamics Conditioned Policy
David Rytz, Suyoung Choi, Wanming Yu +3
This article presents Platform Adaptive Locomotion (PAL), a unified control method for quadrupedal robots with different morphologies and dynamics. We leverage deep reinforcement l…
Discovery of skill switching criteria for learning agile quadruped locomotion
Wanming Yu, Fernando Acero, Vassil Atanassov +4
This paper develops a hierarchical learning and optimization framework that can learn and achieve well-coordinated multi-skill locomotion. The learned multi-skill policy can switch…