Abstract

The problem of collision avoidance of an unmanned aerial vehicle (UAV) group is studied in this paper. A collision avoidance method of UAV group formation based on second-order consensus algorithm and improved artificial potential field is proposed. Based on the method, the UAV group can form a predetermined formation from any initial state and fly to the target position in normal flight, and can avoid collision according to the improved smooth artificial potential field method when encountering an obstacle. The UAV group adopts the “leader–follower” strategy, that is, the leader UAV is the controller and flies independently according to the mission requirements, while the follower UAV follows the leader UAV based on the second-order consensus algorithm and formations gradually form during the flight. Based on the second-order consensus algorithm, the UAV group can achieve formation maintenance easily and the Laplacian matrix used in the algorithm is symmetric for an undirected graph. In the process of obstacle avoidance, the improved artificial potential field method can solve the jitter problem that the traditional artificial potential field method causes for the UAV and avoids violent jitter. Finally, simulation experiments of two scenarios were designed to verify the collision avoidance effect and formation retention effect of static obstacles and dynamic obstacles while the two UAV groups fly in opposite symmetry in the dynamic obstacle scenario. The experimental results demonstrate the effectiveness of the proposed method.

Highlights

  • Group control issues have long been recognized as a very important part of a multi-agent system.Because in the near future, it will become more and more common for unmanned robots to replace people in a cluster to perform difficult tasks

  • The basic method is that the Unmanned aerial vehicle (UAV) moves in the direction in which the potential field drops at the fastest velocity [1]

  • When the relative distance is greater than the maximum working distance, the obstacle has no force on the UAV

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Summary

Introduction

Group control issues have long been recognized as a very important part of a multi-agent system. Collision avoidance technology is the basic problem to be considered in cluster control [5,6] In response to those problems, this paper studies and analyzes the collision avoidance technology in the case of formation maintenance. The artificial potential field method has the characteristics of high computational efficiency and good real-time performance. It is widely used under real-time control conditions. The method proposed in this paper is based on the collision avoidance strategy of consensus strategy and artificial potential field method. Based on this method, the UAV cluster can quickly restore the formation while avoiding collision

Graph Theory
Artificial Potential Field Method
Formation Control Continuous Time Domain Model
Discretized Data Processing
Path Optimization Based on Improved Artificial Potential Field Method
Method
Static Obstacle Scene
Relative
Dynamic Obstacle Scene
10. Relative
Conclusions
Full Text
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