A Robust Path Planning For Mobile Robot Using Smart Particle Swarm Optimization

被引：46

作者：

Dewang, Harshal S. ^{[1
]}

Mohanty, Prases K. ^{[1
]}

Kundu, Shubhasri ^{[2
]}

机构：

[1] Natl Inst Technol, Yupia 791112, Arunachal Prade, India

[2] KIIT Univ, Bhubaneswer 751024, India

来源：

INTERNATIONAL CONFERENCE ON ROBOTICS AND SMART MANUFACTURING (ROSMA2018) | 2018年 / 133卷

关键词：

Particle Swarm Optimization (PSO); Mobile Robot; Path Planning; Obstacle Avoidance; NAVIGATION;

D O I：

10.1016/j.procs.2018.07.036

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new approach is presented for getting a solution of the mobile robot path planning problem based on Adaptive Particle Swarm Optimization (APSO). The proposed APSO algorithm is smarter than conventional PSO and widely used for solving the real time problems. In this work an objective function is framed considering the distance between robot to goal and obstacle respectively. The objective function is optimized with of APSO for solving the path planning process of robot. The different simulated experiments are performed to test the ability of the proposed algorithm. The performance of the robot path planning using APSO is compared to the performance of the conventional PSO in terms path length and time in static environments. It is focused that using new approach the robot can successfully avoid obstacle and reach the target with shorter time than conventional PSO. (C) 2018 The Authors. Published by Elsevier Ltd.

引用

页码：290 / 297

页数：8

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