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Proceedings ArticleDOI

An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot

TLDR
A new APF method for path-planning of mobile robots in a dynamic environment where the target and obstacles are moving is proposed, and the new force function and the relative threat coefficient function are defined.
Abstract
The artificial potential field (APF) method is widely used for autonomous mobile robot path planning due to its simplicity and mathematical elegance. However, most researches are focused on solving the path-planning problem in a stationary environment, where both targets and obstacles are stationary. This paper proposes a new APF method for path planning of mobile robots in a dynamic environment where the target and obstacles are moving. Firstly, the new force function and the relative threat coefficient function are defined. Then, a new APF path-planning algorithm based on the relative threat coefficient is presented. Finally, computer simulation and experiment are used to demonstrate the effectiveness of the dynamic path-planning scheme.

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Book ChapterDOI

Path Planning in RoboCup Soccer Simulation 3D Using Evolutionary Artificial Neural Network

Saleha Raza, +1 more
TL;DR: The results suggest that the neural network evolved via PSO based approach performs better than the other variations of neural networks as well as the baseline approach.
Proceedings ArticleDOI

A Method for Trajectory Planning of Mobile Robot in Random Obstacles Environment

TL;DR: An improved method for trajectory planning of mobile robot in random obstacle environments using a combination of first local then global path planning and a quantum-behaved particle swarm optimization algorithm is presented.
Proceedings ArticleDOI

Optimized targeting of magnetic nano particles for drug delivery system

TL;DR: Simulation results showed that proposed algorithm has higher success rate in targeting the drugs with a faster convergence rate towards the optimal solution.
Journal ArticleDOI

Path Planning for Mobile Robots in Irregular Environment Using Immune Evolutionary Algorithm

TL;DR: The results of simulation experiment show that immune evolution algorithm is feasible and efficient, because it enhances the performance and quality of mobile robot path planning.
References
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Journal ArticleDOI

Real-time obstacle avoidance for manipulators and mobile robots

TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
Book

Robot Motion Planning

TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Book

Real-time obstacle avoidance for manipulators and mobile robots

TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
Journal ArticleDOI

Dynamic Motion Planning for Mobile Robots Using Potential Field Method

TL;DR: A new potential field method for motion planning of mobile robots in a dynamic environment where the target and the obstacles are moving is proposed and the problem of local minima is discussed.
Journal ArticleDOI

New potential functions for mobile robot path planning

TL;DR: New repulsive potential functions are presented by taking the relative distance between the robot and the goal into consideration, which ensures that the goal position is the global minimum of the total potential.
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