Distributed control of multi-agent systems under communication constraints : application to robotics

Multi-agent systems (MAS) have gained much popularity due to their vast range of applications. MAS is deployed to achieve more complex goals which could not be realized by a single agent alone. Communication and information exchange among the agents in a MAS is crucial to control its cooperative behavior. Agents share their information with their neighbors to reach a common objective, thus do not require any central monitoring unit. However, the communication among the agents is subject to various practical constraints. These constraints include irregular and asynchronous sampling periods and the availability of partial states only. Such constraints pose significant theoretical and practical challenges. In this thesis, we investigate two fundamental problems related to distributed cooperative control, namely consensus and formation control, of double-integrator MAS under these constraints. It is considered that each agent in the network can measure and transmit its position state only at nonuniform and asynchronous sampling instants. Moreover, the velocity and acceleration are not available. First, we study the problem of distributed control of leader-following consensus. A continuous-discrete time observer based leader-following algorithm is proposed. The observer estimates the position and velocity of the agent and its neighbor in continuous time from the available sampled position data. Then these estimated states are used for the computation of the control input. Both fixed and switching topology scenarios are discussed. Secondly, a consensus based distributed formation tracking protocol is designed to achieve both fixed and time-varying formation patterns. Collision avoidance problem is also studied in this thesis. An Artificial Potential Function (APF) based collision avoidance mechanism is incorporated with the formation tracking algorithm to prevent collisions between the agents while converging to a desired position. Finally, the proposed algorithms are applied on a multi-robot network, consisting of differential drive robots using Robot Operating System (ROS). A new scheme is proposed to deal with nonholonomic constraints of the robot. Efficiency of the designed algorithms and their effectiveness in real world applications are shown through both simulation and hardware results.