6 papers
ParkingTransformer: LLM-Enhanced End-to-End Trajectory Planning for Autonomous Parking
Hauteng Wu, Xu Li, Dong Kong +4
End-to-end autonomous parking has emerged as a critical task within the realm of autonomous driving. However, existing methods suffer from black-box characteristics, lacking high-l…
Domain-Adaptive Model Merging Across Disconnected Modes
Junming Liu, Yusen Zhang, Rongchao Zhang +2
Learning across domains is challenging when data cannot be centralized due to privacy or heterogeneity, which limits the ability to train a single comprehensive model. Model mergin…
MPTF-Net: Multi-view Pyramid Transformer Fusion Network for LiDAR-based Place Recognition
Shuyuan Li, Zihang Wang, Xieyuanli Chen +5
LiDAR-based place recognition (LPR) is essential for global localization and loop-closure detection in large-scale SLAM systems. Existing methods typically construct global descrip…
Wild-Drive: Off-Road Scene Captioning and Path Planning via Robust Multi-modal Routing and Efficient Large Language Model
Zihang Wang, Xu Li, Benwu Wang +7
Explainability and transparent decision-making are essential for the safe deployment of autonomous driving systems. Scene captioning summarizes environmental conditions and risk fa…
The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms
Lingdong Kong, Shaoyuan Xie, Zeying Gong +135
Autonomous systems are increasingly deployed in open and dynamic environments -- from city streets to aerial and indoor spaces -- where perception models must remain reliable under…
LVD-GS: Gaussian Splatting SLAM for Dynamic Scenes via Hierarchical Explicit-Implicit Representation Collaboration Rendering
Wenkai Zhu, Xu Li, Qimin Xu +4
3D Gaussian Splatting SLAM has emerged as a widely used technique for high-fidelity mapping in spatial intelligence. However, existing methods often rely on a single representation…