The Path Planning Algorithm Based on the Improved Genetic Algorithm and the Artificial Potential Field Algorithm

Guo, Zengyuan; Qin, Junqi; Qiao, Yuxin; Liu, Shi Yue; Liu, Jianying

doi:10.1190/nsgapc2013-163

Cited by 1 publication

(2 citation statements)

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“…The gravitational field that exists between the robot and the destination is mathematically represented by Equation ( 5), where the constant 'k' indicates the intensity of the gravitational potential field, X denotes the position vector of the robot, and 𝑋𝑋 𝑔𝑔 signifies the target position within the potential field. The attractive force that guides the robot towards the target is modeled by the negative gradient of the target potential function [14]:…”

Section: Gravitational Fieldmentioning

confidence: 99%

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Path planning algorithm based on Improved Artificial Potential Field method

Zhang

2023

ACE

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The domain of research and development concerning mobile robot obstacle avoidance continues to remain an active area of interest. Artificial potential fields (APF) are a common and effective method for obstacle avoidance path planning, where the robot is guided to the target location by a simulated environmental potential field. Traditional artificial potential field methods tend to trap robots in local minima, impeding their ability to reach the goal. This research endeavours to introduce a new approach, the Improved Artificial Potential Field (IAPF) algorithm, which incorporates the A-star method in constructing the artificial potential field. This technique more effectively addresses the issue of path planning for mobile robots, thereby avoiding local minimum solutions. Through simulation experiments in different scenarios, the feasibility of the IAPF algorithm of this paper is verified. The results show that, compared with the traditional APF method, the IAPF algorithm can solve problem of local minimum and plan a sensible path.

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Section: Gravitational Fieldmentioning

confidence: 99%

“…Conversely, if the distance exceeds 𝜌𝜌 0 , the repulsive potential field will have no effect on the robot's motion. [14]:…”

Section: Repulsion Fieldmentioning

confidence: 99%