9 papers
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…
NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning
Ruihua Han, Shuai Wang, Shuaijun Wang +8
Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision avoidance. This paper presents N…
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…
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…
Agentic Self-Evolutionary Replanning for Embodied Navigation
Guoliang Li, Ruihua Han, Chengyang Li +5
Failure is inevitable for embodied navigation in complex environments. To enhance the resilience, replanning (RP) is a viable option, where the robot is allowed to fail, but is cap…
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…