Abstract
Aiming at the problem that the particle swarm optimization (PSO) algorithm easy to fall into the local optimum. Combining the advantages of local search of bacterial foraging optimization algorithm (BFO), this paper introduces the chemotaxis and dispersal operation of the bacterial foraging algorithm into the PSO algorithm to obtain hybrid algorithm. This paper applies the hybrid algorithm to 3D path planning. The simulation results show that the hybrid algorithm effectively improves the PSO algorithm’s defects that are easy to fall into local optimal, improves the optimization efficiency and accuracy of the algorithm, and shows good performance in 3D path planning.
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Wang, Y., Wang, S. (2020). 3D Path Planning Based on Improved Particle Swarm Optimization Algorithm. In: Kountchev, R., Patnaik, S., Shi, J., Favorskaya, M. (eds) Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology. Smart Innovation, Systems and Technologies, vol 179. Springer, Singapore. https://doi.org/10.1007/978-981-15-3863-6_6
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DOI: https://doi.org/10.1007/978-981-15-3863-6_6
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