5 papers
Embedding Classical Balance Control Principles in Reinforcement Learning for Humanoid Recovery
Nehar Poddar, Stephen McCrory, Luigi Penco +3
Humanoid robots remain vulnerable to falls and unrecoverable failure states, limiting their practical utility in unstructured environments. While reinforcement learning has demonst…
Stability-Aware Retargeting for Humanoid Multi-Contact Teleoperation
Stephen McCrory, Romeo Orsolino, Dhruv Thanki +2
Teleoperation is a powerful method to generate reference motions and enable humanoid robots to perform a broad range of tasks. However, teleoperation becomes challenging when using…
Anticipatory and Adaptive Footstep Streaming for Teleoperated Bipedal Robots
Luigi Penco, Beomyeong Park, Stefan Fasano +7
Achieving seamless synchronization between user and robot motion in teleoperation, particularly during high-speed tasks, remains a significant challenge. In this work, we propose a…
Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning
Zhaoyuan Gu, Junheng Li, Wenlan Shen +15
Humanoid robots hold great potential to perform various human-level skills, involving unified locomotion and manipulation in real-world settings. Driven by advances in machine lear…
Mixed Reality Teleoperation Assistance for Direct Control of Humanoids
Luigi Penco, Kazuhiko Momose, Stephen McCrory +4
Teleoperation plays a crucial role in enabling robot operations in challenging environments, yet existing limitations in effectiveness and accuracy necessitate the development of i…