A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments
Ullah, Zakir1,3; Xu, Zhiwei1,3; Lei, Zhang1; Zhang, Libo2
刊名SYMMETRY-BASEL
2018-05-01
卷号10期号:5页码:20
关键词wheeled mobile robot (WMR) RL DecaWave tracking localization PF tag anchor RTLS wheel-slip estimation
ISSN号2073-8994
DOI10.3390/sym10050149
英文摘要A novel approach is proposed for the path tracking of a Wheeled Mobile Robot (WMR) in the presence of an unknown lateral slip. Much of the existing work has assumed pure rolling conditions between the wheel and ground. Under the pure rolling conditions, the wheels of a WMR are supposed to roll without slipping. Complex wheel-ground interactions, acceleration and steering system noise are the factors which cause WMR wheel slip. A basic research problem in this context is localization and slip estimation of WMR from a stream of noisy sensors data when the robot is moving on a slippery surface, or moving at a high speed. DecaWave based ranging system and Particle Filter (PF) are good candidates to estimate the location of WMR indoors and outdoors. Unfortunately, wheel-slip of WMR limits the ultimate performance that can be achieved by real-world implementation of the PF, because location estimation systems typically partially rely on the robot heading. A small error in the WMR heading leads to a large error in location estimation of the PF because of its cumulative nature. In order to enhance the tracking and localization performance of the PF in the environments where the main reason for an error in the PF location estimation is angular noise, two methods were used for heading estimation of the WMR (1): Reinforcement Learning (RL) and (2): Location-based Heading Estimation (LHE). Trilateration is applied to DecaWave based ranging system for calculating the probable location of WMR, this noisy location along with PF current mean is used to estimate the WMR heading by using the above two methods. Beside the WMR location calculation, DecaWave based ranging system is also used to update the PF weights. The localization and tracking performance of the PF is significantly improved through incorporating heading error in localization by applying RL and LHE. Desired trajectory information is then used to develop an algorithm for extracting the lateral slip along X- and Y-axis from the PF estimated position of the WMR, the lateral slip along X- and Y-axis is then used to take some corrective measures. Lateral slip information is also used to find the direction along which WMR has to move to get back along the desired trajectory. Simulation results show that our proposed LHE and RL heading estimation methods significantly improve the PF localization and tracking performance on a slippery surface in both indoor and outdoor environments. The simulation results also show that the accurate locations of WMR and desired path information are used to estimate and compensate the lateral slip.
资助项目CAS-TWAS President's Ph.D. Fellowship Programme, University of Chinese Academy of Sciences ; Innovation Project of Institute of Computing Technology, Chinese Academy of Sciences
WOS研究方向Science & Technology - Other Topics
语种英语
出版者MDPI
WOS记录号WOS:000435196300022
内容类型期刊论文
源URL[http://119.78.100.204/handle/2XEOYT63/5204]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Ullah, Zakir
作者单位1.Univ Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Software, Beijing 100049, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Ullah, Zakir,Xu, Zhiwei,Lei, Zhang,et al. A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments[J]. SYMMETRY-BASEL,2018,10(5):20.
APA Ullah, Zakir,Xu, Zhiwei,Lei, Zhang,&Zhang, Libo.(2018).A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments.SYMMETRY-BASEL,10(5),20.
MLA Ullah, Zakir,et al."A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments".SYMMETRY-BASEL 10.5(2018):20.
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