ContribUtions on Artificial Potential Field Method for Effective Obstacle Avoidance

被引:0
作者
Jean-François Duhé
Stéphane Victor
Pierre Melchior
机构
[1] Univ. Bordeaux,
[2] IMS - UMR 5218 CNRS,undefined
[3] Bordeaux INP,undefined
[4] ENSEIRB-MATMECA,undefined
来源
Fractional Calculus and Applied Analysis | 2021年 / 24卷
关键词
26A33; 34A08; 35R11; 31B15; 44A20; 93D09; 12-02; 12E12; 31-00; path planning; reactive path planning; fractional potential field; Poisson equation; energy consumption; Riemann-Liouville derivative;
D O I
暂无
中图分类号
学科分类号
摘要
Obstacle avoidance is one of the main interests regarding path planning. In many situations (mostly those regarding applications in urban environments), the obstacles to be avoided are dynamical and unpredictable. This lack of certainty regarding the environment introduces the need to use local path planning techniques rather than global ones. A well-known method uses artificial potential fields introduced by Khatib. The Weyl potential definition have enabled to distinguish the dangerousness of an obstacle, however acceleration oscillations appear when the considered robot enters a danger zone close to an obstacle, thus leading to high energy consumption. In order to reduce these oscillations regarding this method, four alternative formulations for the repulsive field are proposed: corrective polynomials, tangential and radial components, Poisson potential and pseudo fractional potential. Their limitations will be explored and their performances will be compared by using criteria such as length and energy in a simulation scenario.
引用
收藏
页码:421 / 446
页数:25
相关论文
共 20 条
[1]  
Ashourian M(2016)Navigation of a mobile robot using a virtual potential field and artificial neural network J. of Artificial Intelligence in Electrical Engineering 5 11-20
[2]  
Garrido S(2010)Robotic motion using harmonic functions and finite elements J. of Intelligent and Robotic Systems 59 57-73
[3]  
Moreno L(2002)Dynamic motion planning for mobile robots using potential field method Autonomous Robots 13 207-222
[4]  
Blanco D(2017)Path planning with fractional potential fields for autonomous vehicles 20th IFAC World Congress (IFAC WC 2017) 50 14533-14538
[5]  
Martín Monar F(2019)New interpretation of fractional potential fields for robust path planning Fract. Calc. Appl. Anal 22 113-127
[6]  
Ge S(2020)Autonomous car decision making and trajectory tracking based on genetic algorithms and fractional potential fields Intelligent Service Robotics 13 315-330
[7]  
Cui Y(2017)Optic flow-based collision-free strategies: From insects to robots Arthropod Structure & Development 46 703-717
[8]  
Moreau J(undefined)undefined undefined undefined undefined-undefined
[9]  
Melchior P(undefined)undefined undefined undefined undefined-undefined
[10]  
Victor S(undefined)undefined undefined undefined undefined-undefined