Optimal Path Planning Based on Hybrid Genetic-Cuckoo Search Algorithm

摘要

Three-dimensional path planning is one of the most important factor to decide the efficiency of the space robot moving. early research through mathematical modeling got some mathematical model to solve this problem. However, With different scenarios of the constraints on the robot path gradually increased. Intelligent algorithm which has global optimization increased advantages and ability to deal with multiple constraints has gradually become the mainstream. In this paper, a hybrid intelligent algorithm-Hybrid Genetic-cuckoo search algorithm is proposed, which can take into account the actual size of the robot and the strong global search ability of the genetic algorithm as the premise, and combine with the adaptive cuckoo algorithm to enhance the local search ability of the algorithm in the later stage, so as to improve the practicability of the intelligent algorithm. Simulation results show that the proposed algorithm can avoid obstacles reasonably in multi-constrained three dimensions (3D) environment, and the result is better than the single intelligent optimization algorithm.