Paper Info
Title
Persistent Connected Power Constrained Surveillance with Unmanned Aerial Vehicles
Abstract
Persistent surveillance with aerial vehicles (drones) subject to connectivity and power constraints is a relatively uncharted domain of research. To reduce the complexity of multi-drone motion planning, most state-of-the-art solutions ignore network connectivity and assume unlimited battery power. Motivated by this and advances in optimization and constraint satisfaction techniques, we introduce a new persistent surveillance motion planning problem for multiple drones that incorporates connectivity and power consumption constraints. We use a recently developed constrained optimization tool (Satisfiability Modulo Convex Optimization (SMC)) that has the expressivity needed for this problem. We show how to express the new persistent surveillance problem in the SMC framework. Our analysis of the formulation based on a set of simulation experiments illustrates that we can generate the desired motion planning solution within a couple of minutes for small teams of drones (up to 5) confined to a 7 × 7 × 1 grid-space.
Year
DOI
Venue
2020
10.1109/IROS45743.2020.9341662
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Keywords
DocType
ISSN
persistent connected power constrained surveillance,unmanned aerial vehicles,power constraints,multidrone motion planning,network connectivity,unlimited battery power,constraint satisfaction,persistent surveillance motion,multiple drones,power consumption constraints,constrained optimization tool,persistent surveillance motion planning,satisfiability modulo convex optimization,SMC
Conference
2153-0858
ISBN
Citations 
PageRank 
978-1-7281-6213-3
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Pradipta Ghosh1134.02
Paulo Tabuada24281264.80
ramesh govindan3154302144.86
Gaurav S. Sukhatme45469548.13