  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.
