Research on Path Planning of Industrial Robots based on Improved Swarm Algorithm

Yuzhou Zhang

doi:10.62051/ay2fh611

Authors

Yuzhou Zhang

DOI:

https://doi.org/10.62051/ay2fh611

Keywords:

Improved Bee Colony Algorithm; Industrial Robots; Path Planning; Adaptive Genetic Algorithm; Combinatorial Optimization.

Abstract

In this paper, a trajectory optimization method of intelligent is designed. Firstly, genetic algorithm based on genetic evolution is used to get the initial value of the population. Path length, number of turns and energy consumption of the moving manipulator were used as evaluation parameters. A new adjustable crossover and mutation operator is proposed. Finally, genetic algorithm, Artificial bee colony algorithm is used to evaluate the proposed method for trajectory optimization of mobile robots. The results can effectively prevent the local minimum, reduce the time spent in the process of robot movement, and greatly improve the efficiency of the motion trajectory.

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