Mobile Robot Path Planning Based on Improved Artificial Potential Field Method
Zhao Tiantian, LI Wei-jie
- Year
- 2018
- Citations
- 33
Abstract
To solve the obstacle avoidance problem of mobile robots in dynamic environment, this paper proposes an improved artificial potential field method to solve the problems such as the unreachability of target points, the slow convergence speed, and the inability to avoid obstacles in real time when traditional artificial potential field methods are used in path planning. The improved algorithm can solve the target point inaccessibility problem by satisfying the robot real-time path planning by introducing the virtual target point and changing the repulsive field function. The simulation results show that compared with the traditional artificial potential field method, the robot can jump out of the local extreme point. The feasibility and effectiveness of the improved algorithm proposed in the dynamic environment to complete the path planning.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991