A Method of Autonomous Robot Navigation in Dynamic Unknown Environment

Meng Wei, Huang Qingcheng, Han Xuedong, and Hong Bingrong

Journal of Computer Research and Development > 2005 > 42(9): 1538-1543.

Meng Wei, Huang Qingcheng, Han Xuedong, and Hong Bingrong. A Method of Autonomous Robot Navigation in Dynamic Unknown Environment[J]. Journal of Computer Research and Development, 2005, 42(9): 1538-1543.

Citation:

PDF (353 KB)

A Method of Autonomous Robot Navigation in Dynamic Unknown Environment

Meng Wei, Huang Qingcheng, Han Xuedong, and Hong Bingrong

(School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001)

More Information

Published Date: September 14, 2005

Graphical Abstract

Abstract

Abstract

An autonomous navigation method of robot in dynamic unknown environment is presented. Human's assistance is used instead of particular description of map. There are two phases in this method, which are human's guiding phase and autonomous navigation phase. In phase of human's guiding, a rough polar coordinate map of local environment is obtained by multi sensor information fusion and through it the global map is obtained. The method of eliminating sensor data error is also given here. According to map obtained in guiding phase, a robot moves in dynamic environment in the phase of autonomous navigation. Constraint condition of robot's motion control and dynamic obstacle avoiding method are also presented. Robot can dispose of emergent obstacles in this method, and optimization of path is also attained. Experiment results show the effectiveness of this method.
- autonomous robot,
- sensor fusion,
- obstacle avoiding

FullText(HTML)

References (0)

[1]	Ren Wei, Wang Zhigang, Yang Hua, Zhang Yisheng, Chen Ming. NeuroSymbolic Task and Motion Planner for Disassembly Electric Vehicle Batteries[J]. Journal of Computer Research and Development, 2021, 58(12): 2604-2617. DOI: 10.7544/issn1000-1239.2021.20211002
[2]	Song Chuanming, Min Xin, Xie Weidong, Yin Baocai, Wang Xianghai. Elastic Motion Estimation Algorithm Using Two-Bit-Depth Pixels[J]. Journal of Computer Research and Development, 2019, 56(11): 2469-2484. DOI: 10.7544/issn1000-1239.2019.20180699
[3]	LiFeng, PanJingkui. Human Motion Recognition Based on Triaxial Accelerometer[J]. Journal of Computer Research and Development, 2016, 53(3): 621-631. DOI: 10.7544/issn1000-1239.2016.20148159
[4]	Liu Weibin, Liu Xingqi, Xing Weiwei, Yuan Baozong. Improving Motion Synthesis by Semantic Control[J]. Journal of Computer Research and Development, 2011, 48(7): 1255-1262.
[5]	Xia Shihong, Wei Yi, and Wang Zhaoqi. A Survey of Physics-Based Human Motion Simulation[J]. Journal of Computer Research and Development, 2010, 47(8): 1354-1361.
[6]	Zong Dan, Li Chunpeng, Xia Shihong, Wang Zhaoqi. Key-Postures Based Automated Construction of Motion Graph[J]. Journal of Computer Research and Development, 2010, 47(8): 1321-1328.
[7]	Zhang Zhixian, Liu Jianhua, and Ning Ruxin. Research on Motion Simulation Realization Technology of Planar Linkage Based on Virtual Environment[J]. Journal of Computer Research and Development, 2010, 47(6): 979-987.
[8]	Yang Yuedong, Wang Lili, and Hao Aimin. Motion String: A Motion Capture Data Representation for Behavior Segmentation[J]. Journal of Computer Research and Development, 2008, 45(3): 527-534.
[9]	Zhao Guoying, Li Zhenbo, Deng Yu, Li Hua. Human Motion Recognition and Simulation Based on Retrieval[J]. Journal of Computer Research and Development, 2006, 43(2): 368-373.
[10]	Wang Zhaoqi, Zhang Yongdong, and Xia Shihong. 3D Human Motion Simulation and a Video Analysis System for Sports Training[J]. Journal of Computer Research and Development, 2005, 42(2).