期刊论文详细信息
ROBOMECH Journal
Self-localization method for mobile robot using acoustic beacons
Koichi Mizutani1  Naoto Wakatsuki1  Keiichi Zempo1  Takuji Kawagishi2  Satoki Ogiso3 
[1] Faculty of Engineering, Information and Systems, University of Tsukuba, Ibaraki, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Ibaraki, Japan;School of Integrative and Global Majors, University of Tsukuba, Ibaraki, Japan
关键词: Self-localization;    Mobile robot;    Acoustic beacons;    Microphone array;   
DOI  :  10.1186/s40648-015-0034-y
学科分类:人工智能
来源: Springer
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【 摘 要 】

In this paper, we have proposed a low-cost self-localization method which uses 4 elements of microphones, wheel rotation and sound sources as beacons, whose absolute location and frequency bands are known. The proposed method consists of following 4 steps. The proposed method (i) execute self-localization using wheel-based odometry, (ii) estimate direction-of-arrival (DOA) of the sound sources using sounds recorded by the elements of the microphone array, (iii) predict the DOA of the sound sources from estimated location and pose, and (iv) conduct self-localization by integrating all of the information. To evaluate the proposed method, experiments were conducted. The proposed method was compared to the conventional methods, which were wheel-based odometry and self-localization using only DOA. In the experiments, we have supposed the house-cleaning robot and its trajectory. As results, without any obstacles or walls, the mean of the estimation errors by wheel-based odometry were 670 mm and 0.08 rad, and those of self-localization using only DOA were 2870 m and 0.07 rad in the worst case. In contrast with these methods, proposed method results in 69 mm, 0.02 rad as the worst estimation error of self location and pose. From the result with occlusion of a sound source, the mean of the localization error increased 60 mm, as the proposed method detects the incorrect DOA and prevents it from estimation. From the result with reflective wave from wall, there was a place where the localization error was large. The cause of this error was considered as directivity of sound source. These results indicate that the proposed method is feasible under indoor environment.

【 授权许可】

CC BY   

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