A Developed Firefly Algorithm for Multi-Objective Path Planning Optimization Problem

Effective path planning is the basis of autonomous navigation for mobile robots. In this paper, a multi-objective path planning optimization method that mainly realized by the developed firefly algorithm is proposed. First, the environment is modeled by grid map. Grid extension is realized to ensure the safety of planned path. Second, Pareto-dominance is employed to balance the performance of optimized solutions. In addition, elite record library is created to reserve the non-dominance solutions. Different evolutionary operators are carried out to search the optimal solutions. Third, path length and path smoothness are selected as two important optimization objectives. To verify the efficiency and performance of the developed optimization algorithm, the well-known ZDT1 instance is tested in advance. Moreover, the canonical NSGA-II is also used to solve the path planning problem in the same conditions. Finally, compared results verify the effectiveness of the proposed method.