3 papers
cs.HC2025
RESPOND: Risk-Enhanced Structured Pattern for LLM-driven Online Node-level Decision-making
Dan Chen, Heye Huang, Tiantian Chen +4
Current LLM-based driving agents that rely on unstructured plain-text memory suffer from low-precision scene retrieval and inefficient reflection. To address this limitation, we pr…
cs.RO2025
SMART: Scalable Multi-Agent Reasoning and Trajectory Planning in Dense Environments
Heye Huang, Yibin Yang, Wang Chen +3
Multi-vehicle trajectory planning is a non-convex problem that becomes increasingly difficult in dense environments due to the rapid growth of collision constraints. Efficient expl…
cs.CV2025
MetaSSC: Enhancing 3D Semantic Scene Completion for Autonomous Driving through Meta-Learning and Long-sequence Modeling
Yansong Qu, Zixuan Xu, Zilin Huang +3
Semantic scene completion (SSC) is essential for achieving comprehensive perception in autonomous driving systems. However, existing SSC methods often overlook the high deployment…