UAV Formation Obstacle Avoidance Control Algorithm Based on Improved Artificial Potential Field and Consensus

Abstract

Aiming at the problem of UAV formation's obstacle avoidance and the consensus of position and velocity in a 3D obstacle environment, a novel distributed obstacle avoidance control algorithm for cooperative formation based on the improved artificial potential field (IAPF) and consensus theory is proposed in this paper. First, the particle model of the UAV and the dynamic model of the second-order system are established, and the topological structure of the communication network of the system is described with the knowledge of graph theory. Second, the attractive potential field function containing the coordination gains factor, the repulsive potential field function containing the influence factor of the repulsive force and the planning angle, and the potential field function between the UAVs containing the communication weight are defined. Then, the variables of position and velocity in the consensus protocol are improved by the reference vector of the formation center and the expected velocity, respectively, and a new formation obstacle avoidance control protocol is designed by combining the IAPF and the theory of consensus. Finally, the Lyapunov function is used to prove the stable convergence of the algorithm. The simulation results show that this method can not only prevent the UAV from colliding with each other while avoiding static and dynamic obstacles but also enable the UAV to quickly restore the expected formation and achieve the consensus of the relative distance, relative height, and velocity.

Research on Distributed Real-Time Formation Tracking Control of High-Order Multi-UAV System

“…The principle of the traditional APF was introduced in [6]; therefore, it is not repeated in this paper.…”

“…Consensus implies that each UAV will eventually converge its state to the same value through information interaction [5]. For example, [6] designed a second-order formation control algorithm combining the potential field…”

“…From the above discussion, it is clear that the formation tracking control of low-order multi-agent systems was studied in [6]- [18]. The fixed track of the leader is preset, and offline tracking control of the follower to the leader is finally realized.…”

“…Therefore, it has more engineering application value than the multi-UAV system in the form of a formation to track moving targets in real time and efficiently avoid obstacles. Aiming at the above problems, the repulsive potential field function of reference [6] was further improved. The obstacle mass was introduced into the repulsive potential field function.…”

“…The obstacle mass was introduced into the repulsive potential field function. A new third-order real-time formation-tracking control protocol was designed based on the control protocol in [6]. The leader can fly in real time under the driving of the potential field, and the follower can autonomously generate the desired formation under the action of the tracking control protocol, avoid obstacles safely, and follow the leader in real time in the form of a formation.…”