Decentralized Control of Three-Dimensional Mobile Robotic Sensor Networks

TL;DR

This paper addresses decentralized control and coverage algorithms for mobile robotic sensor networks operating in three-dimensional spaces, introducing novel algorithms for coverage, search, target localization, and formation building with proven convergence.

Contribution

It presents new decentralized algorithms for 3D coverage, search, and formation control of robotic sensor networks, with rigorous convergence proofs and extensive simulations.

Findings

Decentralized algorithms achieve complete 3D coverage.

Bio-inspired search algorithms effectively locate static and mobile targets.

Convergence to desired formations is mathematically proven.

Abstract

Decentralized control of mobile robotic sensor networks is a fundamental problem in robotics that has attracted intensive research in recent decades. Most of the existing works dealt with two-dimensional spaces. This report is concerned with the problem of decentralized self-deployment of mobile robotic sensor networks in three-dimensional environments. The first part of the report investigates the problem of complete sensing coverage in three-dimensional spaces. We propose a decentralized random algorithm to drive mobile robotic sensors on the vertices of a truncated octahedral grid for complete sensing coverage of a bounded 3D area. In the second part, we present a distributed random algorithm for search in bounded three-dimensional environments. Third, we study the problem of locating static and mobile targets in a bounded 3D space by a network of mobile robotic sensors. We introduce a novel decentralized bio-inspired random search algorithm for finding static and mobile objects in 3D areas. This algorithm combines the Levy flight random search mechanism with a 3D covering grid. This report studies the problem of 3D formation building in 3D spaces by a network of mobile robotic sensors. Decentralized consensus-based control law for the multi-robot system which results in forming a given geometric configuration from any initial positions in 3D environments is proposed. Convergence of the mobile robotic sensors to the given configurations are shown by extensive simulations. Moreover, a mathematically rigorous proof of convergence of the proposed algorithms to the given configurations are given.