Distributed Cooperative Avoidance Control for Multi-Unmanned Aerial Vehicles

Abstract

It is well-known that collision-free control is a crucial issue in the path planning of unmanned aerial vehicles (UAVs). In this paper, we explore the collision avoidance scheme in a multi-UAV system. The research is based on the concept of multi-UAV cooperation combined with information fusion. Utilizing the fused information, the velocity obstacle method is adopted to design a decentralized collision avoidance algorithm. Four case studies are presented for the demonstration of the effectiveness of the proposed method. The first two case studies are to verify if UAVs can avoid a static circular or polygonal shape obstacle. The third case is to verify if a UAV can handle a temporary communication failure. The fourth case is to verify if UAVs can avoid other moving UAVs and static obstacles. Finally, hardware-in-the-loop test is given to further illustrate the effectiveness of the proposed method. IntroductionCurrently, the cooperative control of a multiple unmanned aerial vehicle (UAV) system is attracting growing interest. This is motivated by the constantly growing number of civil and commercial UAV applications [1]. One of the core problems in multi-UAV systems is motion planning, where each UAV navigates a path to the target by sharing each other's information. This should result in a collision-free path derived from UAV motion control. This has driven the development of various UAV collision avoidance algorithms.UAV collision avoidance necessitates a way to predict UAV motion. There are different methods to predict UAV motion and the future positions of the UAV. Early collision avoidance strategies focus on the static obstacles [2,3], using decision trees to avoid various troublesome situations [4], and using path planning to avoid the obstacles [5]. As moving obstacles are more often found in a real environment, many techniques have been proposed for dealing with this situation. For example, in [6], the authors developed a vision-based collision avoidance method by using minimum effort guidance. In [7], the authors presented a reactive avoidance method by using nonlinear differential geometric guidance; in [8,9], the authors developed a local path planning method for UAV navigation; in [10], the authors presented a collision avoidance algorithm by using dynamic programming; in [11], the authors proposed a collision avoidance algorithm based on potential fields; in [12][13][14][15][16][17], the authors presented the velocity obstacle method for deconflicting the UAV paths. Among these methods, the velocity obstacle has been the most actively studied in multi-UAV control over the past ten years. These include methods from avoidance maneuver based on conflict geometry [12]; optimal reciprocal collision avoidance [13]; reciprocal collision avoidance using on-board decentralized sensing without communication [16]; the recursive probabilistic velocity obstacles algorithm [14]; the hybrid reciprocal 1 2 of 25 velocity obstacle algorithm [15]; and the artificial bee colony optimized reciprocal velocity obstacle alg...

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“…Noncooperative strategies lack prior knowledge of communication barriers, whereas cooperative approaches rely on cooperative communication among UAVs to exchange information. For instance, passive sensors are used in non-cooperative approaches to detect and avoid obstacles, while another noncooperative avoidance method proposed in [197] assumes that the obstacle's detachment, instructions, and rapidity variation are known. Cooperative approaches are preferred in multi-UAV systems for personal protection and design flexibility.…”

Reservation-Based 3D Intersection Traffic Control System for Autonomous Unmanned Aerial Vehicles

“…In relation to reactive online path planning, the works in [34][35][36][37][38][39][40] use an online collision avoidance algorithm that relies on the sensors of the UAVs to detect the obstacles. In [34], when an obstacle is detected, an escape point algorithm is used to find a waypoint that will avoid the obstacle, and then the UAV will move towards the goal again after reaching the waypoint.…”

“…The concept of velocity obstacle is used in [37] to find a path away from the detected obstacle. In [38], a decentralized cooperative control scheme was devised. UAV heartbeat messages are used to enable cooperative communication and velocity obstacle is used to avoid obstacles.…”