Haptic assisted aircraft optimal assembly path planning scheme based on swarming and artificial potential field approach

2014 ◽  
Vol 69 ◽  
pp. 18-25 ◽  
Author(s):  
Syed Hassan ◽  
Jungwon Yoon
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Field Approach ◽  
Planning Scheme ◽  
Optimal Assembly

Distributed path planning of a multi-robot system based on the neighborhood artificial potential field approach

SIMULATION ◽  
2018 ◽  
Vol 95 (7) ◽  
pp. 637-657 ◽  
Author(s):  
Fethi Matoui ◽  
Boumedyen Boussaid ◽  
Mohamed Naceur Abdelkrim
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Artificial Potential Field ◽  
Robot System ◽  
Field Approach ◽  
Multi Robot

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.

An Optimization Path Planning Method Based on Evolutionary Artificial Potential Field

2013 ◽  
Vol 380-384 ◽  
pp. 1414-1417
Author(s):  
Fei Long Li
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Local Minimum ◽  
Minimum Point ◽  
Artificial Potential Field ◽  
Minimum Problem ◽  
Field Approach ◽  
Local Minimum Point ◽  
The Matrix ◽  
Local Minimum Problem

This paper presents an evolutionary way for the robot to plan path. The way is based on the Evolutionary Artificial Potential Field approach. APF is an efficient way for a robot to plan its path, and the evolutionary APF can help the robot to jump out of the local minimum point. A matrix is integrated in the new algorithm. The matrix can modify the direction of a robot when the robot is trapped in a local minimum point. The force which has been changed will prompt the robot to escape from the local minimum point. Simulation result shows that the optimized algorithm is an effective way to solve the local minimum problem.

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