Lattice flocking of multi-quadrotor system: an algorithm based on artificial potential field

This paper investigates the flocking and obstacle avoidance problem of multi-quadrotor system with a lattice-type structure. To tackle nonlinear dynamics and cooperative consensus of a swarm of quadrotors, we proposed two algorithms (one for free flocking and one for constrained flocking) based on artificial potential field with two cooperative strategies using position tracking and attitude tracking, respectively. Firstly, the inner-loop control model of single quadrotor is provided. Then, we build an artificial potential function to act on the coordinate variable. Third, obstacle avoidance term is added to the flocking algorithm proposed previously. Finally, the position and attitude are taken as the coordinate variables, respectively, to both two algorithms, one for optimizing the distance of each quadrotor until the lattice-type structure is formed and keeping continuously and another for optimizing the distance between quadrotor and obstacles to avoid collision. Simulation results demonstrate the validity of both algorithms.