规模化无人集群共识模型与协同控制方法

doi:10.12382/bgxb.2024.0869

摘要/Abstract

摘要：

针对无人系统难以应用于复杂任务场景的难题,将群体智能涌现作为研究出发点,以四旋翼无人机为研究对象,开展规模化无人集群共识模型与协同控制方法研究。设计感知视角空间剖分下的邻居优选机制和自吸引互排斥机制,生成集群空间构型,结合观点动力学中社会共识的形成机理构建观点综合机制,实现集群速度同步。提出自主分群、合群机制和主动规避与安全避障结合的避障方法,灵活调整集群规模以适应密集障碍物环境和多目标场景。验证结果表明,所提方法在仿真平台上可以应用于50架无人机的分布式集群,在多障碍物的室内、森林和城镇环境下,10架无人机集群能以5m/s的飞行速度安全穿越障碍区;所提方法在实物平台上可以应用于4架无人机的分布式集群,同时安全穿越室内障碍物区域,验证了集群模型的有效性。

关键词: 无人集群, 共识协同, 主动规避, 安全避障, 观点综合

Abstract:

The unmanned systems are difficult to perform a mission in complex scenarios.The consensus models and collaborative control methods for large-scale unmanned cluster are studied by taking the emergence of swarm intelligence as the starting point of the research and the quadrotor drones as the research object.A neighbor selection mechanism and an adaptive attraction and mutual repulsion mechanism for the spatial partitioning of perception perspective are designed to generate the cluster spatial configuration.Combining the formation mechanism of social consensus in opinion dynamics,a view synthesis mechanism is constructed to achieve cluster speed synchronization.The autonomous group separation and aggregation rules are proposed and an obstacle avoidance method that combines active avoidance and safe strategy are proposed,so that the cluster size is flexibly adjusted to adapt to the dense obstacle environments.Simulated results show that the proposed method can be applied to a distributed cluster of 50 UAVs.In indoor,forest and urban environments with multiple obstacles,a cluster of 10 drones can safely cross an obstacle zone at a flight speed of 5m/s.The proposed method can be also applied to a distributed cluster of 4 UAVs which can safely traverse indoor obstacle zones,verifying the effectiveness of the cluster model.

Key words: unmanned cluster, consensus coordination, active avoidance, safe obstacle avoidance, opinion synthesis

李诗颖, 丁应和, 孙海文, 许正, 李烨, 唐恩博. 规模化无人集群共识模型与协同控制方法[J]. 兵工学报, 2024, 45(S2): 113-122.

LI Shiying, DING Yinghe, SUN Haiwen, XU Zheng, LI Ye, TANG Enbo. Consensus Model and Collaborative Control Method of Large-scale Unmanned Cluster[J]. Acta Armamentarii, 2024, 45(S2): 113-122.

图/表 17

图1 无人机的欧拉角示意图

Fig.1 Schematic diagram of Euler angle of UAV

图2 集群遇到障碍物分离图

Fig.2 Separation of unmanned cluster when encountering an obstacle

图3 邻居视角为40°时四旋翼无人机集群实验

Fig.3 Quadrotor UAV cluster experiment with neighbor’s viewing angle of 40 degrees

图4 室内密集场景下无人机集群穿越过程(左为集群穿越第1排障碍物,右为集群穿越第2排障碍物)

Fig.4 Process of UAV cluster crossing the obstacles in indoordense scenes(left:the group crossing the first row of obstacles,right:the group crossing the second row of obstacles)

图5 室内密集场景下无人机集群飞行轨迹

Fig.5 Flight trajectory of UAV cluster in indoor dense scenes

图6 室内密集场景下穿越过程的邻居间距图

Fig.6 Neighbor distance diagram in indoor dense scenes

图7 室内密集场景下穿越过程的飞行速度图

Fig.7 Flight speed diagram in indoor dense scenes

图8 森林仿真场景(左为穿越前,右为穿越后)

Fig.8 Forest simulation scene(left:before crossing, right:after crossing)

图9 森林仿真场景的飞行轨迹

Fig.9 Flight trajectory in forest simulation scene

图10 森林仿真场景的邻居间距图

Fig.10 Neighbor distance diagram in forest simulation scene

图11 森林仿真场景的飞行速度图

Fig.11 Flight speed diagram in forest simulation scene

图12 城镇仿真场景的飞行轨迹

Fig.12 Flight trajectory in city simulation scene

图13 城镇仿真场景的邻居间距图

Fig.13 Neighbor distance diagram in city simulation scene

图14 城镇仿真场景的飞行速度图

Fig.14 Flight speed diagram in city simulation scene

图15 4架实物无人机(左为实物实验场景,右为真实无人机模型)

Fig.15 Four UAVs(left:physical experiment scene. right:real UAV model)

图16 飞行轨迹俯视图

Fig.16 Top view of flight trajectory

图17 4架无人机真实飞行轨迹

Fig.17 Real flight trajectories of four UAVs

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