A robust iterative pose tracking method assisted by modified visual odometer. Issue 1 (30th November 2020)

• Record Type: Journal Article
• Authors: Yuan, Rupeng; Zhang, Fuhai; Fu, Yili; Wang, Shuguo
• Is Part Of: Sensor review. Volume 41:Issue 1(2021)
• Page Start: 1
• Page End: 15
• Publication Date: 2020-11-30
• Subjects: Mobile robot -- Pose tracking -- Error compensation -- Sensors -- Robotics -- Localization -- Lasers; Sensor systems -- Periodicals; Detectors -- Industrial applications -- Periodicals; Engineering instruments -- Periodicals; 681.2
• DOI: 10.1108/SR-01-2020-0005
• Languages: English
• ISSNs: 0260-2288

Abstract

Abstract : Purpose: The purpose of this paper is to propose a robust iterative LIDAR-based pose tracking method assisted by modified visual odometer to resist initial value disturbance and locate a robot in the environments with certain occlusion. Design/methodology/approach: At first, an iterative LIDAR-based pose tracking method is proposed. The LIDAR information is filtered and occupancy grid map is pre-processed. The sample generation and scoring are iterated so that the result is converged to the stable value. To improve the efficiency of sample processing, the integer-valued map indices of rotational samples are preserved and translated. All generated samples are analyzed to determine the maximum error direction. Then, a modified visual odometer is introduced for error compensation. The oriented fast and rotated brief (ORB) features are uniformly sampled in the image. A local map which contains key frames for reference is maintained. These two measures ensure that the modified visual odometer is able to return robust result which compensates the error of LIDAR-based pose tracking method in the maximum error direction. Findings: Three experiments are conducted to prove the advantages of the proposed method. The proposed method can resist initial value disturbance with high computational efficiency, give back credible real-time result in the environment with abundant features and locate a robot in the environment with certain occlusion. Originality/value: The proposed method is able to give back real-time pose tracking results with robustness. The iterative sample generation enables the robot to resist initial value disturbance. In each iteration, rotational and translational samples are separately generated to enhance computational efficiency. The maximum error direction of LIDAR-based pose tracking method is determined by principle component analysis and compensated by the result of modified visual odometer to give back correct pose in the environment with certain occlusion.