Cooperative Formation and Obstacle Avoidance Algorithm for Multi-UAV System in 3D Environment

• Published in: Chinese Control Conference pp. 6943 - 6948
• Main Authors: Lin, Qianyu, Wang, Xiaoli, Wang, YuTong
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 01.07.2018
• Subjects: Clustering algorithms; Collision avoidance; Force; improved artificial potential field method; information consensus; obstacle avoidance; Safety; Topology; UAV formation; Unmanned aerial vehicles
• ISSN: 1934-1768
• DOI: 10.23919/ChiCC.2018.8483113

Multi-UAV cooperative formation has become a hot research issue. Up to now, obstacles and other UAVs are still the main factors that threaten the flight safety. In this paper, we present a solution for formation flight and obstacle avoidance of unmanned aerial vehicles (UAVs) which can achieve cluster situational awareness, autonomous formation control and intelligent collaborative decision making. The main idea of this algorithm is to consider all UAV members as a whole and control the internal and external of the UAV system separately. Inside the system, a communication topology is set up. They use consensus algorithm to keep formation and avoid collision between UAVs. Moreover, we use the weight coefficient to set the priority for every UAV. Outside the system, an improved artificial potential field method is built for UAV system. We improved the safety distance and the traditional artificial potential to make them more suitable for the UAV obstacle avoidance task. Even when UAVs reach obstacles at high speed and small angle, they will have enough time and space to change flight direction. The internal control algorithms and external control algorithms are integrated to form the virtual total force by modifying the Reynolds clustering rules. Three track instructions are obtained from this virtual force. Finally, the effectiveness of cooperative obstacle avoidance algorithm is proved by MATLAB.