A hybrid algorithm combining bidirectional alternating search algorithm (BASA*) and improved genetic algorithm (IGA) is proposed to solve the single path planning problem with finite target points. A bidirectional alternate search mechanism with a search buffer region is introduced to improve the path search efficiency of the A* algorithm in a large-scale environment, and a heuristic function is improved by considering the proportion of obstacles to enhance the evaluation ability of the algorithm in a complex environment; The IGA is used to transform the multi-task path planning into a discrete optimization problem, and BASA* is used to generate the coding path between the task points, combined with the random ergodic sampling selection operation, partial matching crossover and mutation operation, and the fitness function considering the energy constraint is used to determine the optimal access order of the target points. The simulation results show the effectiveness of the proposed hybrid algorithm, which can provide a technical reference for robot multi-task operation.