Abstract
Presently, the path planning and obstacle avoidance of unmanned aerial vehicle (UAV) are attracting research field. A variety of techniques have been introduced by the researchers for obtaining optimal path and avoiding obstacles in the path. This paper presents the implementation of adaptive differential evolution (DE) algorithm for collision avoidance as well as obtaining the optimal path in a static environment whereas former being given more importance. Compared to classical DE algorithm, the proposed adaptive DE allows the UAV to reach the target in an optimal path while avoiding obstacles in a collective manner. The overall performance of the proposed algorithm is verified by simulation results.
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Nagendra Kumar, P., Mohanty, P.K., Kundu, S. (2020). Path Planning and Obstacle Avoidance of UAV Using Adaptive Differential Evolution. In: Deepak, B., Parhi, D., Jena, P. (eds) Innovative Product Design and Intelligent Manufacturing Systems. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2696-1_104
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DOI: https://doi.org/10.1007/978-981-15-2696-1_104
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