Human-Oriented Opportunistic Control for Time-Varying Formation of NASVs With Opportunistic-Moving Leader and Intermittent Human–Computer Interactions

In this paper, we study the problem of the time-varying formation of the networked autonomous surface vehicles (NASVs) with opportunistic-moving leader based on the intermittent human-computer interactions. The presence of the opportunistic-moving leader means that the leader maneuverably completes the human-assigned and real-time changing tasks (such as obstacle avoidance, target surrounding control) during the movement. To solve the above problem, we propose a hierarchical human-oriented opportunistic control (HHOOC) algorithm via using the intermittent human-computer interactions to satisfy the demands of humans for rest or reaction pauses. The presented algorithm can force the leader to complete the time-varying human-assigned tasks and control the followers to achieve the time-varying formation. In the HHOOC algorithm, the components constituting task information are known only to the humans, but not to the ASVs, which is beneficial to ensure the confidentiality and security of the task. Based on the theories of convex optimization and Lyapunov criteria, the sufficient conditions on the control gains are presented to guarantee the convergence to optimal solution. Finally, the effectiveness of the HHOOC algorithm is verified by several simulations.