Path planning of mobile robot based on hybrid improved artificial fish swarm algorithm

The artificial fish swarm algorithm is easy to fall into the local optimum for robot global path planning. A hybrid improved Artificial Fish Swarm Algorithm (HIAFSA) is proposed. Firstly, the sub-optimal path is determined by A* algorithm, and then the adaptive behavior of artificial fish swarm algorithm is improved based on the inertia weight factor, and the attenuation function α is introduced to improve the visual range and moving step length of the artificial fish, balance the global path planning and local path planning, and further improve the convergence speed and quality of the solution. The experimental results show that the hybrid improved artificial fish swarm algorithm has been improved in avoiding local optimum, convergence speed and precision

Path planning of mobile robot based on hybrid improved artificial fish swarm algorithm

The artificial fish swarm algorithm is easy to fall into the local optimum for robot global path planning. A hybrid improved Artificial Fish Swarm Algorithm (HIAFSA) is proposed. Firstly, the sub-optimal path is determined by A* algorithm, and then the adaptive behavior of artificial fish swarm algorithm is improved based on the inertia weight factor, and the attenuation function α is introduced to improve the visual range and moving step length of the artificial fish, balance the global path planning and local path planning, and further improve the convergence speed and quality of the solution. The experimental results show that the hybrid improved artificial fish swarm algorithm has been improved in avoiding local optimum, convergence speed and precision