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- W3000740608 abstract "Aiming at the local optimal problem caused by precocious particles in the path planning process of mobile robot by traditional particle swarm optimization algorithm (PSO), a hybrid neural process-pso algorithm was constructed by integrating the idea of motion process prediction into PSO. The main idea is that in the next iteration of particle swarm individuals, the neural process is used to predict the individual location, increasing the diversity of particle swarm at the later stage of the iteration, and avoiding falling into local optimization too early, so as to improve the optimization ability of the algorithm. The improved algorithm is used to solve the robot path planning problem. The experimental results show that the proposed neural process-particle swarm optimization has better path planning ability and better comprehensive performance than the traditional PSO." @default.
- W3000740608 created "2020-01-23" @default.
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- W3000740608 date "2019-10-01" @default.
- W3000740608 modified "2023-09-26" @default.
- W3000740608 title "Path Planning of Mobile Robot Based on Neural Process-Particle Swarm Optimization" @default.
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- W3000740608 doi "https://doi.org/10.1109/aiam48774.2019.00151" @default.
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