Abstract
This paper demonstrates the use of genetic programming (GP) for the development of mobile robot wall-following behaviors. Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. Navigation algorithms are tested in a variety of differently shaped environments to encourage the development of robust solutions, and reduce the possibility of solutions based on memorization of a fixed set of movements. A brief introduction to GP is presented. A typical wall-following robot evolutionary cycle is analyzed, and results are presented. GP is shown to be capable of producing robust wall-following navigation algorithms that perform well in each of the test environments used.
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References
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Dain, R.A. Developing Mobile Robot Wall-Following Algorithms Using Genetic Programming. Applied Intelligence 8, 33–41 (1998). https://doi.org/10.1023/A:1008216530547
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DOI: https://doi.org/10.1023/A:1008216530547