Hydropower plant underwater inspection robot path planning based on improved hybrid motion sparrow search algorithm

Path planning for underwater remotely operated vehicle(ROV) is a prerequisite for underwater inspection operation of hydropower station. Aiming at the complex environment under the reservoir of power station and the existing path planning algorithms that have the problems of long planning time, poor stability of algorithms, easy to fall into the local optimum, and the generation of paths that are not smooth, this paper puts forward a path planning method for hydropower station ROV based on the improved hybrid motion sparrow search algorithm. Firstly, the good point set is introduced to improve the sparrow population initialization method, which improves the population diversity; secondly, the hybrid motion strategy is proposed to optimize the sparrow population position updating method, which improves the algorithm's convergence accuracy and stability; then, the multivariate objective function, which contains time cost, path threat, current disturbance and penalty function, is established by combining with the actual engineering problems and considering the factors of large underwater flow velocity of reservoirs, strong magnetic field, obstacles, and the cost of input; finally, the triple B-spline interpolation is used to obtain the optimal smooth path. Finally, the optimal smooth path is obtained by three times B-spline interpolation. The simulation results show that compared with other path planning algorithms, the proposed method performs better in terms of computational accuracy, convergence speed and stability, and is suitable for underwater inspection tasks of hydropower stations.