Fuzzy control of a mobile robot for obstacle avoidance

1988 ◽  
Vol 45 (2) ◽  
pp. 231-248 ◽  
Author(s):  
Tomoyoshi Takeuchi ◽  
Yutaka Nagai ◽  
Nobuyoshi Enomoto
2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110264
Author(s):  
Jiqing Chen ◽  
Chenzhi Tan ◽  
Rongxian Mo ◽  
Hongdu Zhang ◽  
Ganwei Cai ◽  
...  

Among the shortcomings of the A* algorithm, for example, there are many search nodes in path planning, and the calculation time is long. This article proposes a three-neighbor search A* algorithm combined with artificial potential fields to optimize the path planning problem of mobile robots. The algorithm integrates and improves the partial artificial potential field and the A* algorithm to address irregular obstacles in the forward direction. The artificial potential field guides the mobile robot to move forward quickly. The A* algorithm of the three-neighbor search method performs accurate obstacle avoidance. The current pose vector of the mobile robot is constructed during obstacle avoidance, the search range is narrowed to less than three neighbors, and repeated searches are avoided. In the matrix laboratory environment, grid maps with different obstacle ratios are compared with the A* algorithm. The experimental results show that the proposed improved algorithm avoids concave obstacle traps and shortens the path length, thus reducing the search time and the number of search nodes. The average path length is shortened by 5.58%, the path search time is shortened by 77.05%, and the number of path nodes is reduced by 88.85%. The experimental results fully show that the improved A* algorithm is effective and feasible and can provide optimal results.


Author(s):  
Baoyu Shi ◽  
Hongtao Wu

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.


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