Research on Obstacle Avoidance Trajectory Control Method of Forest Fire Fighting Robot Based on Improved Fuzzy Theory
Zeyu Sun, Liu Haiping, Qi Zhang
- 发表年份
- 2022
- 引用次数
- 1
摘要
Forest fire is one of the major natural disasters, which seriously threatens the life safety of firefighters. Forest firefighting robots with autonomous mobility are expected to be a solution, but this places high demands on the robot's ability to avoid obstacles. In this paper, an improved fuzzy control algorithm is proposed to improve the robot's obstacle avoidance ability. The kinematic model of forest firefighting robot is first established based on the method of extended Kalman filtering, and the obstacle avoidance kinematic analysis is carried out according to the model. Subsequently, an improved fuzzy control algorithm is designed based on the model, which realizes the reduction of computing demand and the improvement of obstacle avoidance success rate by combining sensor obstacle avoidance and behavior control. Finally, the effectiveness of the improved fuzzy control algorithm is verified by the forest environment simulation. The results shows that in a simulated forest environment full of ravines and trees, the improved fuzzy algorithm designed could enable the robot to successfully achieve obstacle avoidance.
关键词
相关论文
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