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This paper studies the coverage control problem of an unicycle multi‐agent network with external disturbance in a dynamic environment which is described by a time‐varying density function. It is a challenging task to design a coverage control to simultaneously handle the external disturbance, underactuated model and time‐varying density function. Based on Voronoi partition, we proposed a coverage control approach which can maximize the metric function via robust tracking the Voronoi centroid with external disturbance. It is worth to mentioning that the angle of motion of the unicycle agent can align with the Voronoi centroid in finite time. Finally, the effectiveness of the proposed control is shown by simulation results.

In this work, we studied the area coverage control problem (ACCP) based on the time cost metric of a robot network with an input disturbance in a dynamic environment, which was modeled by a time-varying risk density function. A coverage control method based on the time cost metric was proposed. The area coverage task that considers the time cost consists of two phases: the robot network is driven to cover the task area with a time-optimal effect in the first phase; the second phase is when the accident occurs and the robot is driven to the accident site at maximum speed. Considering that there were movable objects in the task area, a time-varying risk density function was used to describe the risk degree at different locations in the task area. In the presence of the input disturbance, a robust controller was designed to drive each robot, with different maximum control input values, to the position that locally minimized the time cost metric function in a fixed time, and the conditions for maximum control input were obtained. Finally, simulation results and comparison result are presented in this paper.

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