The Multiple Unmanned Air Vehicle Persistent Surveillance Problem: A Review

Nikhil Nigam

doi:10.3390/machines2010013

Abstract

Control of autonomous vehicles for applications such as surveillance, search, and exploration has been a topic of great interest over the past two decades. In particular, there has been a rising interest in control of multiple vehicles for reasons such as increase in system reliability, robustness, and efficiency, with a possible reduction in cost. The exploration problem is NP hard even for a single vehicle/agent, and the use of multiple vehicles brings forth a whole new suite of problems associated with communication and cooperation between vehicles. The persistent surveillance problem differs from exploration since it involves continuous/repeated coverage of the target space, minimizing time between re-visits. The use of aerial vehicles demands consideration of vehicle dynamic and endurance constraints as well. Another aspect of the problem that has been investigated to a lesser extent is the design of the vehicles for particular missions. The intent of this paper is to thoroughly review the persistent surveillance problem, with particular focus on multiple Unmanned Air Vehicles (UAVs), and present some of our own work in this area. We investigate the different aspects of the problem and slightly digress into techniques that have been applied to exploration and coverage, but a comprehensive survey of all the work in multiple vehicle control for search, exploration, and coverage is beyond the scope of this paper.

Highlights

There has been growing interest in control and coordination of autonomous vehicles in the fields of Artificial Intelligence (AI) and controls
The authors of this paper have addressed this issue by using an optimizer to determine the space decomposition where the metric is the overall system objective obtained through simulations [55]
The formulation of the problem is key to efficient space decomposition, especially when using generic optimization. We investigated this issue for rectangular partitions, and developed a novel partioning scheme as opposed to choosing the vertices of the rectangle as optimization parameters

Summary

Introduction

There has been growing interest in control and coordination of autonomous vehicles in the fields of Artificial Intelligence (AI) and controls. Fukunaga, and Kahng [2] provide a broad survey of mobile robotics with emphasis on the mechanism of cooperation They give a taxonomical organization of literature based on problems and solutions, while identifying five research axes: group architecture, resource conflict, origin of cooperation, learning, and geometric problems. Parker [4] provides a slightly more recent overview of distributed autonomous mobile robotics with particular emphasis on physical implementations. She has identified the following areas of research interest in mobile robotics: biological inspirations, communication architectures, localization/mapping/exploration, object transport and manipulation, motion coordination, reconfigurable robots, and learning. Chandler and Pachter [6] discuss research issues, pertaining to autonomous control of tactical UAVs

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Conclusion