14 citations · 24 across the 12 of their papers we have counts for
12 papers
Free-Init: Scan-Free, Motion-Free, and Correspondence-Free Initialization for Doppler LiDAR-Inertial Systems
Mingle Zhao, Jiahao Wang, Tianxiao Gao +2
Robust initialization is crucial for online systems. In the letter, a high-frequency and resilient initialization framework is designed for LiDAR-inertial systems, leveraging both…
FMCW-LIO: A Doppler LiDAR-Inertial Odometry
Mingle Zhao, Jiahao Wang, Tianxiao Gao +2
Conventional LiDAR-inertial odometry (LIO) or simultaneous localization and mapping (SLAM) methods heavily rely on geometric features of environments, as LiDARs primarily provide r…
Night-Rider: Nocturnal Vision-aided Localization in Streetlight Maps Using Invariant Extended Kalman Filtering
Tianxiao Gao, Mingle Zhao, Chengzhong Xu +1
Vision-aided localization for low-cost mobile robots in diverse environments has attracted widespread attention recently. Although many current systems are applicable in daytime en…
Why semantics matters: A deep study on semantic particle-filtering localization in a LiDAR semantic pole-map
Yuming Huang, Yi Gu, Chengzhong Xu +1
In most urban and suburban areas, pole-like structures such as tree trunks or utility poles are ubiquitous. These structural landmarks are very useful for the localization of auton…
GSB: Group Superposition Binarization for Vision Transformer with Limited Training Samples
Tian Gao, Cheng-Zhong Xu, Le Zhang +1
Vision Transformer (ViT) has performed remarkably in various computer vision tasks. Nonetheless, affected by the massive amount of parameters, ViT usually suffers from serious over…
MaskRange: A Mask-classification Model for Range-view based LiDAR Segmentation
Yi Gu, Yuming Huang, Chengzhong Xu +1
Range-view based LiDAR segmentation methods are attractive for practical applications due to their direct inheritance from efficient 2D CNN architectures. In literature, most range…
Graph Gain: A Concave-Hull Based Volumetric Gain for Robotic Exploration
Zezhou Sun, Huajun Liu, Chengzhong Xu +1
The existing volumetric gain for robotic exploration is calculated in the 3D occupancy map, while the sampling-based exploration method is extended in the reachable (free) space. T…
Ada-Detector: Adaptive Frontier Detector for Rapid Exploration
Zezhou Sun, Banghe Wu, Chengzhong Xu +1
In this paper, we propose an efficient frontier detector method based on adaptive Rapidly-exploring Random Tree (RRT) for autonomous robot exploration. Robots can achieve real-time…
HiTPR: Hierarchical Transformer for Place Recognition in Point Cloud
Zhixing Hou, Yan Yan, Chengzhong Xu +1
Place recognition or loop closure detection is one of the core components in a full SLAM system. In this paper, aiming at strengthening the relevancy of local neighboring points an…
LiDAR Road-Atlas: An Efficient Map Representation for General 3D Urban Environment
Banghe Wu, Chengzhong Xu, Hui Kong
In this work, we propose the LiDAR Road-Atlas, a compactable and efficient 3D map representation, for autonomous robot or vehicle navigation in general urban environment. The LiDAR…
Learning Moving-Object Tracking with FMCW LiDAR
Yi Gu, Hongzhi Cheng, Kafeng Wang +3
In this paper, we propose a learning-based moving-object tracking method utilizing our newly developed LiDAR sensor, Frequency Modulated Continuous Wave (FMCW) LiDAR. Compared with…
Yaw-Guided Imitation Learning for Autonomous Driving in Urban Environments
Yandong Liu, Chengzhong Xu, Hui Kong
Existing imitation learning methods suffer from low efficiency and generalization ability when facing the road option problem in an urban environment. In this paper, we propose a y…