An Intelligent Gain based Ant Colony Optimisation Method for Path Planning of Unmanned Ground Vehicles

Sangeetha Viswanathan; K. S. Ravichandran; Anand M. Tapas; Sellammal Shekhar

doi:10.14429/dsj.69.12509

Sangeetha Viswanathan School of Computing, SASTRA Deemed University, Thirumalaisamudram, Thanjavur - 613 401
K. S. Ravichandran School of Computing, SASTRA Deemed University, Thirumalaisamudram, Thanjavur - 613 401
Anand M. Tapas DRDO-Defence Research and Development Laboratory, Hyderabad - 500 058
Sellammal Shekhar DRDO-Extramural Research and Intellectual Property Rights, DRDO HQrs, New Delhi - 110 004

DOI: https://doi.org/10.14429/dsj.69.12509

Keywords: Ant colony optimisation, Green-ant, Pheromone gain, Collision-free path

Abstract

In many of the military applications, path planning is one of the crucial decision-making strategies in an unmanned autonomous system. Many intelligent approaches to pathfinding and generation have been derived in the past decade. Energy reduction (cost and time) during pathfinding is a herculean task. Optimal path planning not only means the shortest path but also finding one in the minimised cost and time. In this paper, an intelligent gain based ant colony optimisation and gain based green-ant (GG-Ant) have been proposed with an efficient path and least computation time than the recent state-of-the-art intelligent techniques. Simulation has been done under different conditions and results outperform the existing ant colony optimisation (ACO) and green-ant techniques with respect to the computation time and path length.

Author Biographies

Sangeetha Viswanathan, School of Computing, SASTRA Deemed University, Thirumalaisamudram, Thanjavur - 613 401

Ms Sangeetha V. has received her BE (Computer Science Engineering) from Government College of Engineering, Salem and ME (Software Engineering) from Anna University Regional Centre, Coimbatore. She is currently doing her PhD in SASTRA Deemed University. Her areas of interest include Optimisation, nature inspired algorithms, machine learning.

In the current work, she has contributed to the design and implementation of the algorithm and testing.

K. S. Ravichandran, School of Computing, SASTRA Deemed University, Thirumalaisamudram, Thanjavur - 613 401

Dr K.S. Ravichandran received his Master degree from Bharathidasan University and PhD from Alagappa University. He is currently the Associate Dean in School of Computing, SASTRA Deemed University.

His contributions are towards applications of soft computing in the field of image processing, multi-decision criteria making and engineering problems.

Anand M. Tapas, DRDO-Defence Research and Development Laboratory, Hyderabad - 500 058

Mr Anand M. Tapas received his BE (Electrical Engineering) from VRCE, Nagpur, in 1982 and a MTech (Control & instrumentation) from IIT Bombay, India, in 1985. Currently he is working as a Scientist in DRDO-Defence Research & Development Laboratory, Hyderabad. His research interest includes : Missile guidance, control, estimation and instrumentation.

He has contributed in analysing the literature and fine tune the research aspect of the manuscript.

Sellammal Shekhar, DRDO-Extramural Research and Intellectual Property Rights, DRDO HQrs, New Delhi - 110 004

Mrs Sellammal Shekhar, obtained her BTech (Electronics & Communication Engineering) from University of Jodhpur, MTech from IIT Delhi and MS in Cyber Law & Cyber Security from National Law University, Jodhpur. Currently working as Scientist ‘G’ and Associate Director in the Directorate of Extramural Research & Intellectual Property Rights, DRDO Headquarters, New Delhi. Her research interests include: Information Security, cryptology, communication and signal analysis.

In the current study, she has contributed in enhancing the application aspect of the proposed algorithm.

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