A Non-Convex Optimization Approach to Dynamic Coverage Problem of Multi-agent Systems in an Environment with Obstacles

In this paper, a cooperative region reconnaissance problem is investigated where a group of agents are required to fly across and detect events occur in an environment with static obstacles until an effective coverage is achieved. First, the region reconnaissance is formulated as a non-convex optimization problem. A coverage performance index with additional collision and obstacle avoidance constraints is given. Since the optimization index is an implicit function of state variables and cannot be used to compute gradients on state variables directly, an approximate optimization index is selected. Then, a non-convex optimization-based coverage algorithm is proposed to find the optimal reconnaissance location for each agent and guarantee no collisions trajectories among agents and obstacles. Finally, simulation experiments are performed to verify the effectiveness of the proposed approach.