Title: Maze path planning of mobile robots by gradient map rendering and gradient follow

Authors: Arockia Selvakumar Arockia Doss; Arka Das; K.L. Pavan; D. Dinakaran

Addresses: Design and Automation Research Group, School of Mechanical Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu – 600 127, India ' FINCAD Cooperation, ABT 4, 16 Duke Street, Dublin 2, D02X030, Ireland ' School of Mechanical Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India ' Centre for Automation and Robotics, Hindustan Institute of Technology and Science, Chennai, Tamil Nadu, India

Abstract: Path planning for a human being is very easy to reach a desired location in a room, by avoiding obstacles on the way, by generating a mental map and uses this map to find the optimal path. This is a difficult task in case of a robot. In order to make the robot adapt, the system is fed with different obstacle arrangement in the same room and allow the robot to finalise the optimal path avoiding the obstacles. To achieve, the gradient map rendering algorithm is proposed with successful simulation results in MATLAB. The new map produced has given a gradient again using the same algorithm. After the rendering process is completed, the robot climbs up or down the gradient using the maximum or minimum local gradient technique respectively, to find its way to the destination cell. Gradient surface plots are obtained for a variety of mazes to give a visualisation of how the gradient is being formed. Results are obtained after maze simulation successfully shows the most optimised path in any kind of maze.

Keywords: gradient follow; gradient map rendering; gradient movement; grid maze; MATLAB; mobile robot; path planning.

DOI: 10.1504/IJAMECHS.2020.111301

International Journal of Advanced Mechatronic Systems, 2020 Vol.8 No.2/3, pp.57 - 64

Received: 23 Nov 2019
Accepted: 20 Apr 2020

Published online: 19 Nov 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article