3 papers
cs.RO2026
Stage-Transition Dense Reward Modeling for Reinforcement Learning
Yang Yang, Bingjie Chen, Zihan Wang +4
Reinforcement learning for long-horizon robotic manipulation is often limited by sparse and delayed rewards, while manually designing dense shaping signals is costly and brittle to…
cs.RO2026
PhaForce: Phase-Scheduled Visual-Force Policy Learning with Slow Planning and Fast Correction for Contact-Rich Manipulation
Mingxin Wang, Zhirun Yue, Renhao Lu +7
Contact-rich manipulation requires not only vision-dominant task semantics but also closed-loop reactions to force/torque (F/T) transients. Yet, generative visuomotor policies are…
cs.AI2024
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…