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cs.RO2026
Self-Evolutionary Replanning for Failure-Aware Motion Planning
Guoliang Li, Ruihua Han, Chengyang Li +5
Motion planners tuned under nominal conditions can fail when execution conditions change. Existing differentiable adaptation methods provide efficient online updates but remain con…
cs.RO2026
LLM-Driven Scenario-Aware Planning for Autonomous Driving
He Li, Zhaowei Chen, Rui Gao +4
Hybrid planner switching framework (HPSF) for autonomous driving needs to reconcile high-speed driving efficiency with safe maneuvering in dense traffic. Existing HPSF methods ofte…