Dynamic k-coverage planning for multiple events with mobile robots

Abstract

Dynamic k-coverage planning for multiple events with mobile robots is proposed in the article. In mobile sensor networks, movement with the minimum energy for multiple events detection is a challenge which is discussed in the article. The problem of multiple events coverage is divided into two subproblems, namely mobile robots' uniform deployment and nodes' selection. Assuming that sparse mobile robots randomly deploy in the environment, mobile robots need to uniformly deploy firstly in order to effectively communicate with static nodes and extremely cover the entire region. A weighted-sub-Voronoi-halfgravity method and a weighted-sub-Voronoi-half-incenter method are presented for mobile robots' uniform deployment. Two algorithms guarantee mobile robots are deploying with a higher coverage ratio. Meanwhile, analog game theoretic algorithm is proposed for nodes' selection (static node's selection and mobile robots' selection). Only one static node is selected to detect an event and notifies candidate mobile robots which can communicate with the selected one of the event's occurrence. Moreover, k mobile robots are selected for event coverage. The proposed algorithm achieves k-coverage of each event with less energy consumption. Performance analysis and simulations show that the proposed algorithm achieves very good results.