Research on Path Planning of Mobile Robots Based on Snow Ablation Optimizer

Path planning is one of the key technologies for mobile robots. Metaheuristic algorithms hold significant promise in generating an effective and reliable path for mobile robots. However, most metaheuristic algorithms do not balance exploration and exploitation in the solution space, which may lead to premature convergence and cannot guarantee to find a satisfying path. Snow ablation optimizer (SAO) is a novel metaheuristic technique based on the sublimation and melting phenomenon of snow, which can overcome the shortcomings of most other metaheuristic algorithms. This paper proposes a path planning method for mobile robots based on the SAO algorithm and undertakes a comparative study with the planning method based on particle swarm optimization (PSO) using simulation experiments. The results show that the proposed path planner is superior to the PSO-based path planner in both planning speed and path quality.