Team-based Coverage Control of Moving Sensor Networks with Uncertain Measurements
Farshid Abbasi, Afshin Mesbahi, Javad Mohammadpour Velni, Changying Li · 2018
This paper addresses the problem of deploying teams of heterogeneous agents to cover a given environment, where individual agents have access to inaccurate position (measurement) of other agents. Due to their heterogeneity, different uncertainty regions are considered for the agents. A team-based approach is proposed here to minimize an objective function, defined with respect to the probability of events to occur in the environment. The main goal is to take into account inaccurate position information in the design of a control strategy, which is robust and can hence avoid a significant degradation in the coverage performance. To this end, the minimum of all possible distances between agents is considered as the modified distance measure. The immediate consequence of the uncertainty in the agent localization is that the environment is partitioned among teams to avoid overlapping of assigned regions to neighboring teams. The regions assigned to teams is then partitioned among members by implementing a control law with respect to the modified distance measure for avoiding collision. Finally, numerical simulation results examine the effectiveness of the proposed robust team-based partitioning method. Two examples are provided, each of which focuses on a different aspect of heterogeneity in the presence of uncertainty in the data available to the agents.