3 papers
cs.CV2026
Variance-Guided Spatial Attention Fusion for Robust End-to-End Driving under Asymmetric Sensor Degradation
Weizhi Tao, Zengwang Jin, Xiao Wang +1
End-to-end multimodal driving has progressed rapidly by fusing camera and LiDAR streams. Existing pipelines remain fragile under asymmetric sensor degradation, where either an enti…
cs.RO2025
Rich State Observations Empower Reinforcement Learning to Surpass PID: A Drone Ball Balancing Study
Mingjiang Liu, Hailong Huang
This paper addresses a drone ball-balancing task, in which a drone stabilizes a ball atop a movable beam through cable-based interaction. We propose a hierarchical control framewor…
cs.RO2025
Risk-Aware Reinforcement Learning for Autonomous Driving: Improving Safety When Driving through Intersection
Bo Leng, Ran Yu, Wei Han +3
Applying reinforcement learning to autonomous driving has garnered widespread attention. However, classical reinforcement learning methods optimize policies by maximizing expected…