Dynamic path planning of mobile robot based on artificial potential field
Aiming at the problems of gravity imbalance, local minimum and local oscillation in traditional artificial potential field method, an improved artificial potential field algorithm is proposed in this paper. Firstly, the potential field function model is reconstructed; secondly, the pose threshold gain is introduced to overcome the linear interference; finally, the simulated annealing algorithm is used to optimize, and the escape local minimum module is designed to obtain the global optimal solution iteratively, so as to ensure the robot to reach the target quickly and stably. The experimental results show that in the complex environment, the improved artificial potential field method can effectively solve the gravity imbalance, local minimum and local oscillation problems existing in the traditional artificial potential field method, and can make the robot avoid dynamic obstacles and reach the desired target accurately and quickly.
2020 International Conference on Intelligent Computing and Human Computer Interaction (ICHCI)