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5 papers · 1 filter

cs.RO2026

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations

Zhenwei Huang, Changsheng You, Shuai Wang +3

Robot navigation in safety-critical scenarios faces significant challenges from unforeseen semantic events, where collisions arise primarily from the unpredictable behaviors of dyn…

cs.RO2026

Bridging Large-Model Reasoning and Real-Time Control via Agentic Fast-Slow Planning

Jiayi Chen, Shuai Wang, Guangxu Zhu +1

Large foundation models enable powerful reasoning for autonomous systems, but mapping semantic intent to reliable real-time control remains challenging. Existing approaches either…

cs.RO2026

Direct Contact-Tolerant Motion Planning With Vision Language Models

He Li, Jian Sun, Chengyang Li +4

Navigation in cluttered environments often requires robots to tolerate contact with movable or deformable objects to maintain efficiency. Existing contact-tolerant motion planning…

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…