Cooperative Distributed Sensors for Mobile Robot Localization

DOI: 10.4236/wsn.2010.24046   PDF   HTML     7,323 Downloads   11,357 Views   Citations


This paper presents a probabilistic algorithm to collaborate distributed sensors for mobile robot localization. It uses a sample-based version of Markov localization—Monte Carlo localization (MCL), capable of localizing mobile robot in an any-time fashion. During robot localization given a known environment model, MCL method is employed to update robot’s belief whichever information (positive or negative) attained from environmental sensors. Meanwhile, an implementation is presented that uses color environmental cameras for robot detection. All the parameters of each environmental camera are unknown in advance and need be calibrated independently by robot. Once calibrated, the positive and negative detection models can be built up according to the parameters of environmental cameras. A further experiment, obtained with the real robot in an indoor office environment, illustrates it has drastic improvement in global localization speed and accuracy using our algorithm.

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Z. Liang and S. Zhu, "Cooperative Distributed Sensors for Mobile Robot Localization," Wireless Sensor Network, Vol. 2 No. 5, 2010, pp. 347-357. doi: 10.4236/wsn.2010.24046.

Conflicts of Interest

The authors declare no conflicts of interest.


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