4 papers
CushionCatch: A Compliant Catching Mechanism for Mobile Manipulators via Combined Optimization and Learning
Bingjie Chen, Keyu Fan, Qi Yang +6
Catching flying objects with a cushioning process is a skill commonly performed by humans, yet it remains a significant challenge for robots. In this paper, we present a framework…
Safe Expeditious Whole-Body Control of Mobile Manipulators for Collision Avoidance
Bingjie Chen, Yancong Wei, Rihao Liu +5
Whole-body reactive obstacle avoidance for mobile manipulators (MM) remains an open research problem. Control Barrier Functions (CBF), combined with Quadratic Programming (QP), hav…
DeepMF: Deep Motion Factorization for Closed-Loop Safety-Critical Driving Scenario Simulation
Yizhe Li, Linrui Zhang, Xueqian Wang +2
Safety-critical traffic scenarios are of great practical relevance to evaluating the robustness of autonomous driving (AD) systems. Given that these long-tail events are extremely…
Novelty-based Sample Reuse for Continuous Robotics Control
Ke Duan, Kai Yang, Houde Liu +1
In reinforcement learning, agents collect state information and rewards through environmental interactions, essential for policy refinement. This process is notably time-consuming,…