Research on robot path planning based on sparrow search algorithm integrating multiple strategies

The sparrow search algorithm ( SSA ) has some problems in the research of robot obstacle avoidance. It is difficult to jump out of the local optimum in advance, the initial population distribution is not wide enough, and the search accuracy is low. An improved sparrow search algorithm (Sparrow Search Algorithm Combining Butterfly Search and Triangle Walk ,BTSSA) is proposed by introducing a cubic chaotic map to obtain the initial population, introducing a butterfly algorithm and a triangular step strategy to update the individual position, and using a cubic spline curve method to smooth the path.