Path Planning of Multi-Mobile Robot Based on Multistrategy Fusion Improved Sine-Cosine Algorithm

In this paper, an innovative multi-strategy fusion improved sine-cosine algorithm is proposed for multi-mobile robots moving in indoor environments with multiple obstacles. First, the optimization method of the good point set is introduced to improve the diversity of the initial population distribution. Secondly, the Lévy flight strategy is combined with the original cosine algorithm for updating, and the strategy pool is designed for position update mode. The optimal strategy is achieved through roulette. With the increase of iterations, the probability of strategies that can produce expected results is dynamically adjusted through adaptive learning, which improves the optimization performance and effectiveness of the algorithm. Finally, some experimental results are given to illustrate the feasibility and efficiency of the proposed algorithm.