2 citations · 8 across the 8 of their papers we have counts for
6 papers · 1 filter
Fast and Accurate Deep Loop Closing and Relocalization for Reliable LiDAR SLAM
Chenghao Shi, Xieyuanli Chen, Junhao Xiao +2
Loop closing and relocalization are crucial techniques to establish reliable and robust long-term SLAM by addressing pose estimation drift and degeneration. This article begins by…
Deep Reinforcement Learning for Flipper Control of Tracked Robots
Hainan Pan, Bailiang Chen, Kaihong Huang +3
The autonomous control of flippers plays an important role in enhancing the intelligent operation of tracked robots within complex environments. While existing methods mainly rely…
RDMNet: Reliable Dense Matching Based Point Cloud Registration for Autonomous Driving
Chenghao Shi, Xieyuanli Chen, Huimin Lu +3
Point cloud registration is an important task in robotics and autonomous driving to estimate the ego-motion of the vehicle. Recent advances following the coarse-to-fine manner show…
Hybrid Map-Based Path Planning for Robot Navigation in Unstructured Environments
Jiayang Liu, Xieyuanli Chen, Junhao Xiao +3
Fast and accurate path planning is important for ground robots to achieve safe and efficient autonomous navigation in unstructured outdoor environments. However, most existing meth…
ElC-OIS: Ellipsoidal Clustering for Open-World Instance Segmentation on LiDAR Data
Wenbang Deng, Kaihong Huang, Qinghua Yu +3
Open-world Instance Segmentation (OIS) is a challenging task that aims to accurately segment every object instance appearing in the current observation, regardless of whether these…
InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
Neng Wang, Chenghao Shi, Ruibin Guo +3
Identifying moving objects is a crucial capability for autonomous navigation, consistent map generation, and future trajectory prediction of objects. In this paper, we propose a no…