Dynamic Reconfigurable Adaptive UGV Formation System

doi:10.12382/bgxb.2023.0879

Abstract

Abstract:

The formation keeping, reconfiguration and transformation functions of unmanned ground vehicle (UGV) formation systems are studied A hybrid leader-follower strategy is proposed to reduce the dependence on the leading vehicle and ensure the formation integrity. An independent obstacle avoidance function based on vehicle-to-vehicle (V2V) communication for the following vehicles is developed, and a formation node management system is designed manages the attributes of formation members in real time and supports the human-computer interaction. A dynamic extended trajectory planning method with cubic spline curve in three-dimensional space is proposed to generate the following trajectory and realize the obstacle avoidance by acquiring the position information of the front vehicle through V2V communication. The Frenet coordinate system is utilized to decouple the distance keeping and trajectory tracking problems, and the proportional-integral-differential (PID) controller and linear quadratic regulator (LQR) controller are used for longitudinal control and lateral trajectory tracking, respectively. The research results show that the performance of the proposed method can be quickly verifued in the simulation environment built, showing that the method has good performance. And the three functions of the vehicle formation system are verified by real vehicles, and the proposed method is confirmed to have good real-time performance through the stable maintenance of the distance between the vehicles, which is capable of realizing the effective following of the multi-vehicle formation, and shows a high degree of intelligent expansion and adaptability through the transformation of multiple formation shapes as well as the scenarios of members’ joinning and departuring from the vehicle formation.

Key words: unmanned ground vehicle, formation control, vehicle-to-vehicle communication, trajectory planning, trajectory tracking

CLC Number:

U461

JIA Yifei, JIANG Chaoyang. Dynamic Reconfigurable Adaptive UGV Formation System[J]. Acta Armamentarii, 2024, 45(10): 3654-3673.

Figures/Tables 43

Fig.1 Class classification of formation cooperation

Table 1 Advantages and disadvantages of multi-vehicle formation control architecture

控制架构	优点	缺点
集中式	结构简单便于设计;协调能力强;全局最优	容错性差,过于依赖中央处理单元;计算量大,实时性差
分布式	环境适应性强,行为灵活;计算量小,实时性强	局部最优;性能严重依赖通信质量;整体协调能力弱
混合式	协调能力强;全局最优;环境适应性强	实现难度大,设计复杂

Fig.2 Virtual structure approach

Fig.3 Behaviour-based approach

Fig.4 Leading-following method

Table 2 Ability of different formation strategies to deal with major formation problems

方法	保持	避障	重构	抗通信	实时性
虚拟结构法	优	差	差	差	差
基于行为法	差	优	良	良	优
领航跟随法	优	差	良	差	优
图论法	优	良	优	差	差
人工势场法	良	优	差	优	优

Fig.5 Contrast between Frenet coordinate system and Cartesian coordinate system

Fig.6 Control points of basic spline curve

Fig.7 Dynamic extension of spline curves

Fig.8 Longitudinal gap in Frenet coordinate system

Fig.9 Vehicle lateral bicycle model

Fig.10 Lateral error model

Fig.11 Node management system

Fig.12 Schematic diagram of member departure scenario

Fig.13 Member departure flowchart

Fig.14 Scenario of members joinning the vehicle formation

Fig.15 Flowchart of members joinning the vehicle formation

Fig.16 Schematic diagram of adaptive formation generation

Fig.17 Monitoring and manipulating interface

Table 3 Parameter table of formation keeping simulation

参数	数值
起始间隔/m	1.0
期望车间距/m	1.5
最大车速/(m·s^-1)	0.8

Fig.18 Formation trajectories in obstacle-free environment

Fig.19 Gap errors of vehicles in obstacle-free environment

Fig.20 Speed profile of vehicle formation in obstacle-free environment

Fig.21 Comparison of the speed profiles of formation keeping

Fig.22 Comparison of spap errors of formation keeping

Fig.23 Formation trajectory in obstacle environment

Fig.24 Gap errors of vehicles in obstacle environment

Fig.25 Speed profile of vehicle formation in obstacle environment

Fig.26 Driving of vehicle formation presented in the traditional leading-following method in the obstacle area

Fig.27 Driving of vehicle formation presented in the proposed method in the obstacle area

Table 4 Parameter table of formation reconfiguration simulation

参数	数值
起始间隔/m	1.0
期望车间距/m	1.5
巡航车速/(m·s^-1)	0.3

Fig.28 Gap error of vehicles in formation reconfiguration

Fig.29 Speed profile in formation reconfiguration

Fig.30 Formation changing scenario diagram

Fig.31 Protection formation changing scenario

Fig.32 Protective formation changing scenario data graph

Fig.33 Geese-flying formation changing scenario

Fig.34 Changing curves of geese-flying formation

Fig.35 Continuous formation change scene

Fig.36 Experimental site

Table 5 Parameter table of experimental formation reconfiguration

参数	数值
期望车间距/m	1.5
人工平均巡航车速/(m·s^-1)	0.3
出入队阶段临时间距/m	4.
汇入横向误差判断阈值/m	0.2
汇入横摆角判断阈值/(°)	15

Fig.37 Experimental data graph of formation reconfiguration scenario

Fig.38 Experimental data graph of formation changing scenario

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