9 citations · 17 across the 8 of their papers we have counts for
4 papers · 1 filter
RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment
Pou-Chun Kung, Yuan Tian, Zhengqin Li +4
Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most radar SLAM pipelines still rely…
LONER: LiDAR Only Neural Representations for Real-Time SLAM
Seth Isaacson, Pou-Chun Kung, Mani Ramanagopal +2
This paper proposes LONER, the first real-time LiDAR SLAM algorithm that uses a neural implicit scene representation. Existing implicit mapping methods for LiDAR show promising res…
Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities
Pou-Chun Kung, Chieh-Chih Wang, Wen-Chieh Lin
Radar shows great potential for autonomous driving by accomplishing long-range sensing under diverse weather conditions. But radar is also a particularly challenging sensing modali…
A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars
Pou-Chun Kung, Chieh-Chih Wang, Wen-Chieh Lin
Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method a…