Anubhav Kakkar
ABV-Indian Institute of Information Technology and Management, Gwalior

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Multi-robot system using low-cost infrared sensors Anubhav Kakkar; Shivam Chandra; Deepanshu Sood; Ritu Tiwari; Anupam Shukla
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 3: September 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.885 KB) | DOI: 10.11591/ijra.v2i3.pp117-128

Abstract

This paper presents a proposed set of the novel technique, methods, and algorithm for simultaneous path planning, area exploration, area retrieval, obstacle avoidance, object detection, and object retrieval   autonomously by a multi-robot system. The proposed methods and algorithms are built considering the use of low cost infrared sensors with the ultimate function of efficiently exploring the given unknown area and simultaneously identifying desired objects by analyzing the physical characteristics of several of the objects that come across during exploration. In this paper, we have explained the scenario by building a coordinative multi-robot system consisting of two autonomously operated robots equipped with low-cost and low-range infrared sensors to perform the assigned task by analyzing some of the sudden changes in their environment. Along with identifying and retrieving the desired object, the proposed methodology also provide an inclusive analysis of the area being explored. The novelties presented in the paper may significantly provide a cost-effective solution to the problem of area exploration and finding a known object in an unknown environment by demonstrating an innovative approach of using the infrared sensors instead of high cost long range sensors and cameras. Additionally, the methodology provides a speedy and uncomplicated method of traversing a complicated arena while performing all the necessary and inter-related tasks of avoiding the obstacles, analyzing the area as well as objects, and reconstructing the area using all these information collected and interpreted for an unknown environment. The methods and algorithms proposed are simulated over a complex arena to depict the operations and manually tested over a physical environment which provided 78% correct results with respect to various complex parameters set randomly.