Simultaneous localization and mapping algorithm based on point and line features for medical service robots
10.16781/j.0258-879x.2019.05.0507
- Author:
Jing-Dong YANG
1
Author Information
1. Autonomous Robot Lab, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology
- Publication Type:Journal Article
- Keywords:
Medical service robotics;
Oriented FAST and rotated BRIEF;
Simultaneous localization and mapping;
Weak texture scenario
- From:
Academic Journal of Second Military Medical University
2019;40(5):507-511
- CountryChina
- Language:Chinese
-
Abstract:
Objective To propose a point and line (PL)-simultaneous localization and mapping (SLAM) algorithm and to compare it with oriented FAST and rotated BRIEF (ORB)-SLAM2, so as to improve the global localization accuracy and real-time performance of SLAM algorithm for medical service robots. Methods The PL-SLAM algorithm added line features based on point feature in the process of feature extraction, and carried out mapping and global localization in the complex medical environment according to the point and line features after fusion. The public datasets (EuRoc and KITTI) were used to compare the PL-SLAM and ORB-SLAM2 algorithms, and the comprehensive performance of autonomous navigation of the medical service robots was tested. Results Compared with the ORB-SLAM2 algorithm, PL-SLAM algorithm extracted more point and line features in weak texture scenario, and effectively enhanced the global localization accuracy and real-time performance. The rotation error of the PL-SLAM algorithm decreased by 42.2% and the runtime increased by 55.9%. Conclusion PL-SLAM algorithm can effectively improve global localization accuracy and the real-time performance of medical service robots.
