Abstract
This paper proposes an adaptive particle swarm optimization (APSO)-driven algorithm for robot path planning and obstacle avoidance in an unknown environment. The proposed algorithm consists of two different obstacle avoidance methodologies; considering one obstacle at a time and all obstacles in the path between the robot position to the goal position. To avoid collision, the robot determines the tangential points on the safety circle. The simulation results are presented for different environmental situations. The proposed algorithm is applied on Webots, to validate its effectivity. It works efficiently, and the mobile robot has successfully avoided the obstacles while moving toward the goal position. A comparative study between the two obstacle avoidance methodologies is presented in terms of the minimum path length to reach the goal position. The proposed algorithm is also compared with the existing algorithms, and it provides satisfactory result.
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Acknowledgements
This work is supported by Visvesvaraya Ph.D. Scheme, Digital India Corporation for the project entitled “Intelligent Networked Robotic Systems”.
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Himanshu, Singha, A., Kumar, A., Ray, A.K. (2022). Path Planning of Mobile Robot Using Adaptive Particle Swarm Optimization. In: Roy, S., Sinwar, D., Perumal, T., Slowik, A., Tavares, J.M.R.S. (eds) Innovations in Computational Intelligence and Computer Vision . Advances in Intelligent Systems and Computing, vol 1424. Springer, Singapore. https://doi.org/10.1007/978-981-19-0475-2_31
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DOI: https://doi.org/10.1007/978-981-19-0475-2_31
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