1 citations · 1 across the 9 of their papers we have counts for
11 papers
Reactive Real-Time Flow Policies via Asynchronous Distribution Alignment
Moritz Zoellner, Reece O'Mahoney, Ioannis Havoutis +1
Generalist robot policies such as vision-language-action models (VLAs) have achieved remarkable generalization, but their inference delays can conflict with the demands of real-tim…
Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
Zeren Luo, Jiahui Zhang, Yimin Han +4
Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots has been a longstanding challe…
Learning Perceptive Platform Adaptive Locomotion Controllers for Quadrupedal Robots
David Rytz, Kim Tien Ly, Ioannis Havoutis
Universal quadrupedal locomotion remains limited by the difficulty of integrating perception across diverse robot morphologies. State-of-the-art controllers rely on single-robot tr…
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…
Offline Adaptation of Quadruped Locomotion using Diffusion Models
Reece O'Mahoney, Alexander L. Mitchell, Wanming Yu +2
We present a diffusion-based approach to quadrupedal locomotion that simultaneously addresses the limitations of learning and interpolating between multiple skills and of (modes) o…
Constrained Skill Discovery: Quadruped Locomotion with Unsupervised Reinforcement Learning
Vassil Atanassov, Wanming Yu, Alexander Luis Mitchell +2
Representation learning and unsupervised skill discovery can allow robots to acquire diverse and reusable behaviors without the need for task-specific rewards. In this work, we use…
Curriculum-Based Reinforcement Learning for Quadrupedal Jumping: A Reference-free Design
Vassil Atanassov, Jiatao Ding, Jens Kober +2
Deep reinforcement learning (DRL) has emerged as a promising solution to mastering explosive and versatile quadrupedal jumping skills. However, current DRL-based frameworks usually…