4 citations · 21 across the 25 of their papers we have counts for
7 papers · 1 filter
Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots
Feihan Li, Abulikemu Abuduweili, Yifan Sun +3
The control of legged robots, particularly humanoid and quadruped robots, presents significant challenges due to their high-dimensional and nonlinear dynamics. While linear systems…
Absolute State-wise Constrained Policy Optimization: High-Probability State-wise Constraints Satisfaction
Weiye Zhao, Feihan Li, Yifan Sun +4
Enforcing state-wise safety constraints is critical for the application of reinforcement learning (RL) in real-world problems, such as autonomous driving and robot manipulation. Ho…
WeHelp: A Shared Autonomy System for Wheelchair Users
Abulikemu Abuduweili, Alice Wu, Tianhao Wei +1
There is a large population of wheelchair users. Most of the wheelchair users need help with daily tasks. However, according to recent reports, their needs are not properly satisfi…
Physics-Aware Combinatorial Assembly Sequence Planning using Data-free Action Masking
Ruixuan Liu, Alan Chen, Weiye Zhao +1
Combinatorial assembly uses standardized unit primitives to build objects that satisfy user specifications. This paper studies assembly sequence planning (ASP) for physical combina…
Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
Tianhao Wei, Liqian Ma, Rui Chen +2
The requirements for real-world manipulation tasks are diverse and often conflicting; some tasks require precise motion while others require force compliance; some tasks require av…
Implicit Safe Set Algorithm for Provably Safe Reinforcement Learning
Weiye Zhao, Feihan Li, Changliu Liu
Deep reinforcement learning (DRL) has demonstrated remarkable performance in many continuous control tasks. However, a significant obstacle to the real-world application of DRL is…
Real-time Safety Index Adaptation for Parameter-varying Systems via Determinant Gradient Ascend
Rui Chen, Weiye Zhao, Ruixuan Liu +2
Safety Index Synthesis (SIS) is critical for deriving safe control laws. Recent works propose to synthesize a safety index (SI) via nonlinear programming and derive a safe control…