Cooperative Control of Networked Robotic Systems

The main scope of this thesis is the design and analysis of distributed control strategies for achieving optimum area coverage in mobile sensor networks. Due to the numerous applications of the latter in missions as area exploration, environmental sampling, patrolling, or even security, a large part of the scientific community has turned its interest on developing methods for achieving optimum, if possible, sensing environmental perception by groups of autonomous mobile agents. Such robotic teams, randomly deployed in areas of interest initially, are designed to coordinate their motion in a distributed manner, rather than via a global supervisory system, in order to succeed in the corresponding mission objective. At the first stages of this thesis, the coverage problem of an area of interest by a group of identical nodes is examined from a numerical point of view. The mobile nodes are considered to be governed by simple discrete–time kinodynamic motion, while their sensing performance is assumed radial, range–limited, uniform around the node. As a first approach, the optimum direction at each time step for optimum deployment achievement is determined based on proper distance–based space partitioning techniques. The developed concept allows for gradual increase in the covered area among consecutive steps, although suffers from allowing motion of one node at a time. In the sequel, the aforementioned concept is extended to the case of heterogeneous networks, where heterogeneity lays mainly in the unequal limited–range of the sensing performance of the nodes. In addition, extension to continuous–time allows for simultaneous motion of the nodes, increasing drastically the convergence time towards the optimal state, especially for large–scale networks. An alternate partitioning of the space is developed that is mainly based on the nodes’ footprints, rather than their spatial positions only. The resulting assigned cells form the main core for the coordination algorithm proposed, in order to distributedly organize the mobile swarm to achieve optimum sensing performance. Motivated by the high–degree anisotropy that governs the sensing domains of certain types of sensors, i.e. directional microphones for sound sensing mainly for security applications, or even the radiation patterns of directional antennas in communication–coverage scenarios, our research is extended beyond the standard disc model of sensing. Based on certain properties for planar convex curves, a distributed strategy is developed for networks characterized by convex sensing domains of same orientation. Although convexity of the sensing sets may seem to impose a high level restriction to the overall setup, in fact can be assigned as the maximal convex inscribed set in any (originally) anisotropic pattern. The control scheme is further extended, in the sequel, for the case of adding an extra degree of freedom to the node’s mobility abilities, incorporating different and time–varying orientations among the nodes patterns. The resulting scheme is proven to lead anisotropic networks in optimum configurations, considering their sensing footprints, by properly controlling both the nodes’ positions and orientations, via an innovative pattern–based partitioning scheme of the sensed space. The thesis ends by examining the case where radio–range constraints are imposed on inter–agents communication. In the majority of the related works, this issues is usually overcome by allowing RF range as double the sensing one, guaranteeing that way distributed nature of the control schemes. The proposed scheme allows for uncorrelated RF and sensing ranges in the network, while guarantees convergence of the network towards the optimal state, via simultaneous preservation of a–priori imposed radio–range constraints. Concluding remarks along with comparative discussion are presented in the last chapter, where future research plans and ways to improve the already developed schemes are proposed.