zbMATH — the first resource for mathematics

A team-based approach for coverage control of moving sensor networks. (English) Zbl 1372.93008
Summary: The present paper proposes a new team-based approach that allows for forming multiple teams of agents within the coverage control framework. The objective function defined for this purpose tends to minimize the accumulative distance from each agent while reckoning with the given density function that defines the probability of events in the environment to be covered. The proposed team-based approach via the defined optimization problem allows for forming teams of agents when for a variety of reasons, e.g., heterogeneity in their embedded communication capabilities or the dynamics, it is required to keep the similar agents together in the same team. To realize this, the overall objective function is defined as the accumulated sensing cost of individual agents belonging to different teams. The defined collective cost function captures the interdependency of the team’s Voronoi cells on the position of the agents that can be viewed as the impact of the dynamic boundaries on the agents. A gradient descent-based controller is designed to ensure the locally optimum configuration of the teams and agents within each team. The convergence of the proposed method is studied to ensure the stability of the implemented controller in both teams and agents final configuration. In addition, a new formation control approach is proposed using the team-based framework to impose either the same or different formation structures while performing the underlying coverage task. It is shown that maintaining the desired configuration through the proposed formation control is achieved at the cost of sacrificing the sensing performance. Finally, the proposed coverage and formation methods are examined via a numerical example where multiple heterogeneous teams of agents with potentially different number of agents are deployed.

93A14 Decentralized systems
68T42 Agent technology and artificial intelligence
93C95 Application models in control theory
Full Text: DOI
[1] Abbasi, F., Mesbahi, A., & Velni, J.M. (2016). Team-based coverage control of moving sensor networks. In American control conference (pp. 5691-5696). · Zbl 1372.93008
[2] Atınç, G. M.; Stipanović, D. M.; Voulgaris, P. G., Supervised coverage control of multi-agent systems, Automatica, 50, 11, 2936-2942, (2014) · Zbl 1300.93010
[3] Cortes, J.; Martinez, S.; Karatas, T.; Bullo, F., Coverage control for mobile sensing networks, IEEE Transactions on Robotics and Automation, 20, 2, 243-255, (2004)
[4] Kantaros, Y.; Thanou, M.; Tzes, A., Distributed coverage control for concave areas by a heterogeneous robot-swarm with visibility sensing constraints, Automatica, 53, 195-207, (2015) · Zbl 1371.93135
[5] Lee, S.; Diaz, Y.; Egerstedt, M., Multirobot control using time-varying density functions, IEEE Transactions on Robotics, 31, 2, 489-493, (2015)
[6] Nowzari, C.; Cortés, J., Self-triggered coordination of robotic networks for optimal deployment, Automatica, 48, 6, 1077-1087, (2012) · Zbl 1244.93011
[7] Patel, R.; Frasca, P.; Bullo, F., Centroidal area-constrained partitioning for robotic networks, Journal of Dynamic Systems, Measurement, and Control, 136, 3, 137-156, (2013)
[8] Schwager, M.; Rus, D.; Slotine, J., Decentralized, adaptive coverage control for networked robots, International Journal of Robotics Research, 28, 3, 357-375, (2009)
[9] Sharifi, F.; Chamseddine, A.; Mahboubi, H.; Zhang, Y.; Aghdam, A., A distributed deployment strategy for a network of cooperative autonomous vehicles, IEEE Transactions on Control Systems Technology, 23, 2, 737-745, (2015)
[10] Song, C.; Liu, L.; Feng, G.; Xu, S., Coverage control for heterogeneous mobile sensor networks on a circle, Automatica, 63, 349-358, (2016) · Zbl 1329.93092
[11] Stergiopoulos, Y.; Tzes, A., Spatially distributed area coverage optimisation in mobile robotic networks with arbitrary convex anisotropic patterns, Automatica, 49, 1, 232-237, (2013) · Zbl 1257.93007
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.