Event-Triggered Consensus Control for Multirobot Systems With Cooperative Localization

In multirobot systems, the accurate localization of each mobile robot in the team is a prerequisite to reach consensus. This article investigates the problem of event-triggered consensus control for a group of mobile robots based on cooperative localization (CL). In our framework, each robot employs the position estimates from CL to jointly achieve consensus. An event-triggered mechanism based on a mixed-type condition is adopted in order to reduce the frequency of control updates and unnecessary transmission of information between system components. Our goal is to design an event-triggered consensus controller based on CL such that the closed-loop system achieves the prescribed consensus in spite of inaccurate sensor measurements. We provide sufficient conditions that guarantee the desired consensus using eigenvalues and eigenvectors of the Laplacian matrix. We design the controller and filter gains as well as the parameters of the event-triggering mechanism simultaneously in terms of the solution for a linear matrix inequality. Finally, simulation and experimental results are used to demonstrate the effectiveness of proposed approach.

Automated summary

In multirobot systems, accurate localization of each mobile robot is essential for achieving consensus. This article addresses the problem of event-triggered consensus control for a group of mobile robots based on cooperative localization (CL). An event-triggered mechanism using a mixed-type condition is proposed to reduce control updates and unnecessary information transmission. The goal is to design a consensus controller based on CL that ensures the desired consensus despite inaccurate sensor measurements. Eigenvalues and eigenvectors of the Laplacian matrix are used to provide sufficient conditions for the desired consensus. The controller, filter gains, and event-triggering mechanism parameters are designed simultaneously based on a solution to a linear matrix inequality. Simulation and experimental results demonstrate the effectiveness of the proposed approach.