Real‐time motion planning for mobile robots by means of artificial potential field method in unknown environment

2010 ◽  
Vol 37 (4) ◽  
pp. 384-400 ◽  
Author(s):  
Tao Zhang ◽  
Yi Zhu ◽  
Jingyan Song
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Real Time ◽  
Potential Field ◽  
Field Method ◽  
Artificial Potential Field ◽  
Unknown Environment ◽  
Time Motion ◽  
Potential Field Method ◽  
Artificial Potential Field Method

Predictive Artificial Potential Field Method and its Application on Robot Soccer Path Planning

2011 ◽  
Vol 48-49 ◽  
pp. 840-843 ◽  
Author(s):  
Peng Huang ◽  
Chang Yun Miao ◽  
Li Jin Guo ◽  
Ying Li
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Potential Field ◽  
Field Method ◽  
Artificial Potential Field ◽  
Robot Soccer ◽  
Uncertain Environment ◽  
Field Approach ◽  
Potential Field Method ◽  
Artificial Potential Field Method

This paper presents a new predictive artificial potential field approach for robot soccer path planning under complex and uncertain environment. By predicting and analyzing the future position and attitude of concerned object, the position and attitude of the object is controlled by demonstration algorithm. The proposed method is successfully used in the robor soccer shooting and is realized on the MiroSot 3vs3 simulating platform. Experiment results show that this algorithm has good real-time ability and adaptability to environment.

A Mobile Robot Obstacle Avoidance Method Based on Improved Potential Field Method

2013 ◽  
Vol 467 ◽  
pp. 496-501 ◽  
Author(s):  
Hao Wang ◽  
Lian Yu Zhao ◽  
Wei Chen
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Simulation Analysis ◽  
Field Method ◽  
Artificial Potential Field ◽  
Position Information ◽  
Unknown Environment ◽  
Potential Field Method ◽  
Artificial Potential Field Method

Proposing an obstacle avoidance method for mobile robot under unknown environment, which makes use of multiple ultrasonic sensors coordinating with each other and collects position information of obstacles followed by information fuzzy processing, applies artificial potential field method with improved potential function to project the travel path of the robot. It has solved the "deadlock" problem of the traditional artificial potential field method and achieved obstacle avoidance of mobile robot under unknown environment. By simulation analysis, robot obstacle avoidance can be implemented flexibly using this method.

Route planning of intelligent bridge cranes based on an improved artificial potential field method

2021 ◽  
pp. 1-8
Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li
Keyword(s):  
Potential Field ◽  
Autonomous Navigation ◽  
Route Planning ◽  
Simple Algorithm ◽  
Field Method ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Operating Characteristics ◽  
Potential Field Method ◽  
Artificial Potential Field Method

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.

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