Online Defensive Motion Planning Against Adversarial Swarm Attacks using Bernstein Polynomials-Based Model Predictive Control

This paper proposes an online motion planning algorithm for defender drones to protect a High-Value Unit (HVU) against a swarm of attacker drones. We formulate an optimal motion planning problem and approximate its solutions using Bernstein polynomials. The favorable geometric properties of the polynomials allow to compute the cost function and constraints efficiently. Since the attackers' dynamics are generally imperfectly known, we resort to model predictive control (MPC) approach. By predicting future trajectories of the attackers over a short time interval, we calculate optimal trajectories for the defenders to shoot down the attackers and maintain the survival probability of the HVU close to one. This optimization problem is solved recursively with a receding time horizon until the attackers are incapacitated.