A novel A* method fusing bio-inspired algorithm for mobile robot path planning

Abstract

The path planning of mobile robot is to find an optimal collision-free path in time distance or space from the starting point to the target point in a given environment. With the popularization and application of mobile robots, if the efficiency of mobile robots path is not high, the working quality will be seriously affected. How to quickly plan an effective safe path is of great research significance and practical application value. Therefore, we propose a novel A* algorithm based on Bioinspired algorithm for mobile robot path planning. Firstly, the synchronous bidirectional A* algorithm is used to optimize the pheromone of ant colony algorithm, and the transition probability and pheromone update mechanism of ant colony algorithm are improved, so that the global optimization speed of the algorithm is faster and the path length of mobile robot is shortened. Furthermore, the static path is used to initialize the pigeon algorithm. Then, the improved pigeon algorithm is utilized to plan the local path of the mobile robot, and the simulated annealing criterion is introduced to solve the local optimal problem. The logarithmic S-type transfer function is adopted to optimize the step size of the pigeon number, so that the collision with the dynamic obstacles can be better avoided. Finally, a modified B-spline curve is used to smooth and re-plan the path. The simulation results show that the proposed method can realize path planning more effectively in complex dynamic environment.

Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4

“…The Mobile Robot Path Planning Problem aims to plan the shortest trajectory of a mobile robot from its current position to the target position with obstacles collision-free. In order to solve this problem several methods were developed: A hybrid method based on the A* Algorithm with a bio-inspired method is developed in [1] for a mobile robot in static and dynamic environments; a Multi-objective Genetic Algorithm with three criteria (length, security and energy consumption paths) is dedicated for the mobile robot path planning in [2]; an integrated Genetic Algorithm with the Ant Colony Optimization method is proposed for the mobile robot path planning [3]. In this paper the novel optimal method Dhouib-Matrix-SPP (DM-SPP) is enhanced with four movement directions (entitled DM-SPP-4) in order to plan the shortest trajectory for a mobile robot (see figure 1).…”