A practical evaluation of radio signal strength for mobile robot localization

Authors:
Lingfei Wu;Max Q.-H. Meng;Zijing Lin;Wu He;Chao Peng;Huawei Liang
Affiliations:
Center for Biomimetic Sensing and Control Res., Inst. of Int. Mach., Chinese Academy of Sci., Dept. of Automation, Univ. of Science and Techn. of China and The Key Lab. of Biomimetic Sensing and A ...;Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui Province, China;Center for Biomimetic Sensing and Control Res., Inst. of Int. Mach., Chinese Academy of Sci., Dept. of Automation, Univ. of Science and Techn. of China and The Key Lab. of Biomimetic Sensing and A ...;Center for Biomimetic Sensing and Control Res., Inst. of Int. Mach., Chinese Academy of Sci., Dept. of Automation, Univ. of Science and Techn. of China and The Key Lab. of Biomimetic Sensing and A ...;Center for Biomimetic Sensing and Control Res., Inst. of Int. Mach., Chinese Academy of Sci., Dept. of Automation, Univ. of Science and Techn. of China and The Key Lab. of Biomimetic Sensing and A ...;Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui Province, China
Venue:
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Year:
2009

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Abstract

This paper dealt with localization of a mobile robot using received signal strength (RSS) and detailed a practical evaluation about the suitability of the RSS based localization. RSS technique is especially appealing for localization in WSN due to its simplicity such as low cost, size and power constraints, despite of the fact that RSS may bring in very noisy range estimates. We conducted numerous ranging experiments to quantify the effects of various environmental factors on RSS both in the indoor environment and in the outdoor environment. To further improve the localization performance of mobile robot, we proposed a novel improvement---mean filtering technique to reduce the effect of radio irregularity and optimized the localization results. A series of localization experiments were performed to validate the proposed methods, with achieving the localization error to 1.2m in the outdoor basketball field.