Abstract
The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several different locations. The goal, therefore, is to determine the robot’s true initial location while minimizing the distance traveled by the robot. We consider approximation algorithm for the robot localization problem. The algorithm is based on triangulation of a simple polygon representing a map. Based on the basis of the implemented program, we conducted experimental studies of this algorithm. The numerical results and their interpretation are better than others.
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Nam, D.D., Huy, N.Q. (2017). Optimizing the Algorithm Localization Mobile Robot Using Triangulation Map. In: Cong Vinh, P., Tuan Anh, L., Loan, N., Vongdoiwang Siricharoen, W. (eds) Context-Aware Systems and Applications. ICCASA 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-319-56357-2_7
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DOI: https://doi.org/10.1007/978-3-319-56357-2_7
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