scholarly journals Research on Obstacle Avoidance Method for Mobile Robot Based on Multisensor Information Fusion

2020 ◽  
Vol 32 (4) ◽  
pp. 1159
Author(s):  
Chengguo Zong ◽  
Zhijian Ji ◽  
Yan Yu ◽  
Hao Shi
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Information Fusion ◽  
Multisensor Information Fusion

Information Fusion of Ultrasonic Sensor Based on RBF Network in Obstacle-Avoidance System of Mobile Robot

2010 ◽  
Vol 20-23 ◽  
pp. 791-795
Author(s):  
Wei Huang ◽  
Yi Xin Yin ◽  
Shan Ding ◽  
Jie Dong ◽  
Xue Ming Ma ◽  
...  
Keyword(s):  
Neural Networks ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Information Fusion ◽  
Simulation Experiment ◽  
Rbf Networks ◽  
Important Method ◽  
Rbf Network ◽  
Sensor Information ◽  
Made In

Artificial neural networks are applied to multi-sensor information fusion (MSIF) in obstacle-avoidance system of mobile robot. BP and RBF networks are presented, and comparison is made in the simulation experiment. Results show that RBF network is more effective to deal with information of multi-sensor. It can become an important method for multi-sensor information fusion.

scholarly journals Research on path planning of three-neighbor search A* algorithm combined with artificial potential field

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110264
Author(s):  
Jiqing Chen ◽  
Chenzhi Tan ◽  
Rongxian Mo ◽  
Hongdu Zhang ◽  
Ganwei Cai ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Path Length ◽  
Search Time ◽  
Experimental Results ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Neighbor Search

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.

Study of obstacle avoidance based on fuzzy planner for wheeled mobile robot

2011 ◽  
Author(s):  
Suolin Duan ◽  
Yunfeng Li ◽  
Shuyue Chen ◽  
Lanping Chen ◽  
Ling Zou ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Wheeled Mobile Robot
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