publication . Preprint . Conference object . 2018

Synchronous Adversarial Feature Learning for LiDAR based Loop Closure Detection

Peng Yin; Yuqing He; Lingyun Xu; Yan Peng; Jianda Han; Weiliang Xu;
Open Access English
  • Published: 05 Apr 2018
Abstract
Loop Closure Detection (LCD) is the essential module in the simultaneous localization and mapping (SLAM) task. In the current appearance-based SLAM methods, the visual inputs are usually affected by illumination, appearance and viewpoints changes. Comparing to the visual inputs, with the active property, light detection and ranging (LiDAR) based point-cloud inputs are invariant to the illumination and appearance changes. In this paper, we extract 3D voxel maps and 2D top view maps from LiDAR inputs, and the former could capture the local geometry into a simplified 3D voxel format, the later could capture the local road structure into a 2D image format. However, ...
Subjects
free text keywords: Computer Science - Robotics, Simultaneous localization and mapping, Lidar, Ranging, Feature extraction, Feature learning, Computer vision, Image file formats, computer.file_format, computer, Voxel, computer.software_genre, Odometry, Computer science, Control engineering, Artificial intelligence, business.industry, business
Related Organizations
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Preprint . Conference object . 2018

Synchronous Adversarial Feature Learning for LiDAR based Loop Closure Detection

Peng Yin; Yuqing He; Lingyun Xu; Yan Peng; Jianda Han; Weiliang Xu;