Path Planning for Multiple Targets Interception by the Swarm of UAVs based on Swarm Intelligence Algorithms: A Review

Abstract

The dramatic increase in the capabilities and availability of autonomous ground and aerial tools introduces safety and security challenges, particularly in protecting strategic infrastructures. In this context, the interception of multiple mobile threats, aiming to invade restricted spaces of such infrastructures is an important topic. This paper focuses on the problem of path planning for intercepting multiple aerial targets by a swarm of UAVs. 3D path planning for interception of moving targets is a challenging task, in particular when the interception is performed by a swarm of UAVs, as there are multiple kinematic and dynamic constraints. The aim is first to allocate targets to the individual UAVs (task assignment) and to construct a 3D path for each one. Many algorithms have been recognized as noble schemes for solving this kind of problems based on Swarm Intelligence (SI), many of them are based on biological systems such as particle swarm optimization (PSO), ant colony optimization (ACO), artificial bee colony optimization (ABC), bat-inspired algorithm (BA), etc. The paper presents a comprehensive review of SI algorithms centered on the problems related to 3D path planning for target interception by a swarm of UAVs. It also focuses on the improvement of existing SI algorithms for better path optimization. A comprehensive investigation for each algorithm is presented by analyzing its merits and demerits in the context of target interception. This broad review is an outline for scholars and professionals in the field of the swarm of UAVs.

KEYWORDS:

• ABC
• ACO
• BA
• 3D path planning
• PSO
• SI
• UAV

Acknowledgements

Authors are thankful to anonymous reviewers and editor for their suggestions.

Additional information

Notes on contributors

Abhishek Sharma

Abhishek Sharma received the bachelor's degree in electronics and communication engineering from ITM-Gwalior, India, in 2012, and master’s degree in robotics engineering from the University of Petroleum and Energy Studies (UPES), Dehradun, India, in 2014. He was a senior research fellow in a DST funded project under the Technology Systems Development Scheme. He was an assistant professor with the Department of Electronics and Instrumentation, UPES. He is working as a research scientist in Research and Development Department, UPES. His research interests include embedded system, optimization, swarm intelligence and robotics. Email: [email protected]

Shraga Shoval

Shraga Shoval was born in Ramat-Gan, Israel. He studied at “Ohel Shem” high school and received his BSc (1985) and MSc (1987) in Mechanical Engineering from the Technion, Israel Institute of Technology. Between 1987 and 1990 Shraga worked as a scientist in the Commonwealth Scientific and Industrial Research Organization (CSIRO) – Division of Manufacturing Technologies in Sydney, Australia, developing a robotic system for the processing of colored gemstones. He completed his PhD in the University of Michigan, Ann Arbor, at the Department of Mechanical Engineering and Applied Mechanics in 1994. The NavBelt, a navigation device for the blind and visually impaired using mobile robotics technology, that he developed, is one of the first robotic aids for the blind. The NavBelt lead to the development of the GuideCane, that was awarded the best robotics invention by Discover Magazine in 1998. Email: [email protected]

Abhinav Sharma

Abhinav Sharma received his BTech from HNB Garhwal University, Srinagar, India, in 2009 and the MTech from Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India, in 2011. He did his PhD from Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India, in 2016. He is working as an assistant professor (Senior Scale) in the Department of Electrical and Electronics Engineering in University of Petroleum and Energy Studies, Dehradun. His fields of interest include adaptive array signal processing, artificial intelligence, and machine learning, optimization techniques and smart antenna. Corresponding author. Email: [email protected]

Jitendra Kumar Pandey

Jitendra Pandey was born in Bakeware, Uttar Pradesh, India. He received his BSc (Biochemistry, 1996) and MSc (Organic Chemistry, 1998), from the University of Kanpur, India. He received PhD degree from National Chemical Laboratory Pune, in the area of polymer science. He worked as business development manager-International Business SRL Ranbaxy Ltd., Andheri-East, India. He is working as a professor and dean at School of Basic & Applied Science, Adamas University, West Bengal, India. His area of expertise is in polymer nanocomposites, bio-composites, natural nano-particles, water treatment. Email: [email protected]