基于模糊控制的无人机集群视觉着降

在基于视觉导航的自主着降过程中,旋翼无人机受到自身机械振动和复合风场环境等因素的干扰,降落精度低、速度慢,影响集群回收的安全性。针对这一问题,提出一种基于模糊控制和视觉导航的集群自主着降算法。首先无人机集群飞至降落区域后,无人机通过目标检测算法找到自身对应的降落标识,再利用像素距离解算出无人机与对应降落标识间的实际水平距离,然后通过模糊化、模糊推理、去模糊化得到无人机精准对准降落点的控制指令,最终实现集群精准着降。仿真实验与实际飞行实验结果表明,该算法具有更高的鲁棒性,可有效提升无人机集群着降的速度。

Visual Landing System of UAV Swarm Based on Fuzzy Control

In the process of visual navigation based autonomous landing, aimed at the problems that being influenced by its mechanical vibration and compound wind field, rotor unmanned aerial vehicle (UAV) is low in landing accuracy, and slow at speed by means of which swarm recycling safety is affected, a swarm autonomous landing algorithm based on fuzzy control and visual navigation is proposed in this paper. When the UAV swarm is disposed to the landing area, all UAVs can find their corresponding landing marks through the object detection algorithm and calculate the actual horizontal distance to corresponding landing mark by making use of pixel distance, and then the control command of making UAVs into alignment with landing point can be acquired by fuzzification, fuzzy reasoning and defuzzification to realize the accurate landing of swarm. The results of stimulation experiment and actual flight experiment show that the algorithm is highly robust and can improve the speed of the swarm landing of UAVs.