Self-Adaptive Correction of Heading Direction in Stair Climbing for Tracked Mobile Robots Using Visual Servoing Approach

2017 International Conference on Control Engineering and Artificial Intelligence

计算机科学

Ji, Peng^1 ; Song, Aiguo^1 ; Song, Zimo^1 ; Liu, Yuqing^2 ; Jiang, Guohua^2 ; Zhao, Guopu^3

School of Instrument Science and Engineering, Southeast University, Nanjing, China^1

National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, China^2

Jiangsu Siming Engineering Machinery Co. Ltd., Yangzhou, China^3

关键词: Correction algorithms;    Generalization ability;    Hardware resources;    Heading directions;    Majority vote;    Self-Adaptive;    Stair-climbing;    Tracked mobile robots;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/806/1/012005/pdf
DOI  :  10.1088/1742-6596/806/1/012005

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

In this paper, we describe a heading direction correction algorithm for a tracked mobile robot. To save hardware resources as far as possible, the mobile robot's wrist camera is used as the only sensor, which is rotated to face stairs. An ensemble heading deviation detector is proposed to help the mobile robot correct its heading direction. To improve the generalization ability, a multi-scale Gabor filter is used to process the input image previously. Final deviation result is acquired by applying the majority vote strategy on all the classifiers' results. The experimental results show that our detector is able to enable the mobile robot to correct its heading direction adaptively while it is climbing the stairs.