A study on path planning optimization of mobile robots based on hybrid algorithm

The purpose of this study is to develop a novel hybrid meta‐heuristic algorithm for optimal path planning of the mobile robot. A novel hybrid algorithm based on particle swarm optimization (PSO), firefly algorithm (FA), and cuckoo search (CS) is proposed in order to improve the efficiency of algorithms and minimize the cost performance criterion in path planning. First, A MATLAB based interface was designed to easily perform all activities such as generating maps by processing the images taken from the camera, finding paths with algorithms, communicating with robots, and navigating according to path information that the robot determines with algorithms. Second, for path planning in mobile robots, the developed CS‐PSO‐FA hybrid algorithm and CS, FA, PSO algorithms were carried out both simulation and experimentally without hitting obstacles in similar working environments. In addition, various applications are performed in the various simulation environments to verify the developed CS‐PSO‐FA hybrid algorithm and the obtained results are compared. In conclusion, it is demonstrated that the path obtained with the novel hybrid CS‐PSO‐FA algorithm is shorter than CS, PSO, and FA algorithms and thus has a higher performance and the feasibility.