6 papers
RaFD: Flow-Guided Radar Detection for Robust Autonomous Driving
Shuocheng Yang, Zikun Xu, Jiahao Wang +3
Radar has shown strong potential for robust perception in autonomous driving; however, raw radar images are frequently degraded by noise and "ghost" artifacts, making object detect…
Equi-RO: A 4D mmWave Radar Odometry via Equivariant Networks
Zeyu Han, Shuocheng Yang, Minghan Zhu +4
Autonomous vehicles and robots rely on accurate odometry estimation in GPS-denied environments. While LiDARs and cameras struggle under extreme weather, 4D mmWave radar emerges as…
ESCoT: An Enhanced Step-based Coordinate Trajectory Planning Method for Multiple Car-like Robots
Junkai Jiang, Yihe Chen, Yibin Yang +3
Multi-vehicle trajectory planning (MVTP) is one of the key challenges in multi-robot systems (MRSs) and has broad applications across various fields. This paper presents ESCoT, an…
CTS-CBS: A New Approach for Multi-Agent Collaborative Task Sequencing and Path Finding
Junkai Jiang, Ruochen Li, Yibin Yang +4
This paper addresses a generalization problem of Multi-Agent Pathfinding (MAPF), called Collaborative Task Sequencing - Multi-Agent Pathfinding (CTS-MAPF), where agents must plan c…
RINO: Accurate, Robust Radar-Inertial Odometry with Non-Iterative Estimation
Shuocheng Yang, Yueming Cao, Shengbo Eben Li +2
Odometry in adverse weather conditions, such as fog, rain, and snow, presents significant challenges, as traditional vision and LiDAR-based methods often suffer from degraded perfo…
DenserRadar: A 4D millimeter-wave radar point cloud detector based on dense LiDAR point clouds
Zeyu Han, Junkai Jiang, Xiaokang Ding +4
The 4D millimeter-wave (mmWave) radar, with its robustness in extreme environments, extensive detection range, and capabilities for measuring velocity and elevation, has demonstrat…