Safety Guaranteed Optimal Control Policy for Multi-agent Data Harvesting Using a CLF-CBF Approach.

We consider the problem of harvesting data from a set of targets in a wireless sensor network using a collection of mobile agents. The targets lie in a one dimensional mission space and broadcast their data while the agents move overhead. The agents are required to collect all the data and move to terminal locations to offload that data. We use a Hamiltonian analysis to show that the optimal control can be described using a parameterized policy and then develop a gradient descent scheme using infinitesimal perturbation analysis (IPA) to calculate the gradients of the cost function with respect to the control parameters. To avoid collisions between agents, we then apply a Control Lyapunov Function-Control Barrier Function (CLF-CBF) technique to ensure the agents closely track the desired optimal trajectory to complete their mission while avoiding any collisions. Additionally, we analyze the problem of symmetric deadlock in the CLF-CBF controller and show that it can be avoided by adding a small perturbation to the initial and final heights of the agents over the mission space. The approach is demonstrated through simulation.