An UGV Swarm Formation Reconfiguration Method with Space-time Constraints

Abstract

Abstract:

This study proposes a framework for formation reconfiguration of unmanned ground vehicle (UGV) swarm with space-time constraints. The graph theory method was used to describe the coordination relationship of swarm, and the swarm reconfiguration problem was decomposed into the formation transformation problem of the minimum transformation unit. To meet the space constraints of the formation transformation, the study used the model-based predictive path generation algorithm to produce the travelable path that satisfies the initial and final constrains for the UGV. The curve interpolation method was used to create a speed curve that connects the initial and final state smoothly and meets the time constraints. The boundary conditions of speed planning were then proposed based on the collision detection results. Both simulation analysis and vehicle experiments were performed to verify the effectiveness of the proposed swarm reconfiguration method.

Key words: intelligent transportation, space- time constraints, unmanned ground vehicle swarm, formation reconfiguration

摘要：

针对具有时空约束的无人车集群构型变换问题，采用图论方法描述集群协同关系，将集群构型变换问题分解为最小变换单元的队形变换问题. 为满足队形变换的空间约束，运用基于模型的轨迹预测方法为无人车规划提供满足起点和目标点约束的行驶路径，运用曲线插值方法规划平滑且满足时间约束的速度曲线，根据碰撞检测结果提出速度规划的边界条件. 仿真和实车实验证明了构型变换方法的有效性.

关键词: 智能交通, 时空约束, 无人车集群, 构型变换

CLC Number:

TP273.5

SU Zhi-yuan, LI Yong-le, XU You-chun，ZHANG Yong-jin. An UGV Swarm Formation Reconfiguration Method with Space-time Constraints[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 211-217.

苏致远，李永乐，徐友春，章永进. 具有时空约束的无人车集群构型变换方法[J]. 交通运输系统工程与信息, 2020, 20(2): 211-217.

Add to citation manager EndNote|Ris|BibTeX

URL: http://www.tseit.org.cn/EN/abstract/abstract20032.shtml

http://www.tseit.org.cn/EN/Y2020/V20/I2/211

References

[1] 王祥科, 李迅, 郑志强. 多智能体系统编队控制相关问题研究综述[J]. 控制与决策, 2013(11): 1601-1613. [WANG X K, LI X, ZHENG Z Q. Survey of developments on multi-agent formation control related problems[J]. Control and Decision, 2013(11): 1601- 1613.]

[2] 宗群, 王丹丹, 邵士凯, 等. 多无人机协同编队飞行控制研究现状及发展[J]. 哈尔滨工业大学学报, 2017, 49 (3): 1-14. [ZONG Q, WANG D D, SHAO S K, et al. Research status and development of multi UAV coordinated formation flight control[J]. Journal of Harbin Institute of Technology, 2017, 49(3): 1-14.]

[3] CHEN Q Y, LU Y F, JIA G W, et al. Path planning for UAVs formation reconfiguration based on Dubins trajectory[J]. Journal of Central South University, 2018, 25(11): 2664-2676.

[4] WANG D, ZONG Q, TIAN B, et al. Finite-time fully distributed formation reconfiguration control for UAV helicopters[J]. International Journal of Robust Nonlinear Control, 2018, 28(18): 5943-5961.

[5] LIAO F, TEO R, WANG J L, et al. Distributed Formation and Reconfiguration Control of VTOL UAVs [J]. IEEE Transactions on Control Systems Technology, 2016, 25(1): 270-277.

[6] 梁晓龙, 刘流, 何吕龙, 等. 基于固定时间一致性的无人机集群构型变换[J]. 系统工程与电子技术, 2018, 40 (7): 1506-1512. [LIANG X L, LIU L, HE L L, et al. UAV swarm formation reconfiguration based on fixedtime consensus[J]. Systems Engineering and Electronics, 2018, 40(7): 1506-1512.]

[7] 刘流, 梁晓龙, 张佳强, 等. 切换通信拓扑条件下的无人机集群构型变换控制[J]. 兵工学报, 2019, 40(5): 996- 1002. [LIU L, LIANG X L, ZHANG J Q, et al. UAV swarm formation reconfiguration control with switching interaction topologies[J]. Acta Armamentarh, 2018, 40(7): 1506-1512.]

[8] WANG X K, ZENG Z W, CONG Y R. Multi- agent distributed coordination control: Developments and directions via graph viewpoint[J]. Neurocomputing, 2016 (199): 204-218.

[9] RAJAMANI R. Vehicle dynamics and control[M]. New York: Springer Verlag, 2006.

[10] LI X H, SUN Z P , CAO D P, et al. Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles[J]. Mechanical Systems & Signal Processing, 2017(87): 118-137.

[1]	GUO Lie , XU Lin-li, QIN Zeng-ke, WANG Xu. Analysis and Overview of Influencing Factors on Autonomous Driving Takeover [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 72-90.
[2]	XU Meng , LIU Tao , ZHONG Shao-peng , JIANG Yu. Urban Smart Public Transport Studies: A Review and Prospect [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 91-108.
[3]	CHENG Jun, ZHANG Li-yan, CHEN Qi-hong. A Map Aided Visual-inertial Fusion Localization Method for Autonomous Vehicles [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 117-126.
[4]	WANG Guo-dong , LIU Li , MENG Yu , MA Zhi-ping, ZHENG Hao-qing , GU Qing, BAI Guo-xing. Integrated Control of Trajectory Planning and Tracking for Vehicle Collision Avoidance [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 127-136.
[5]	MA Dong-fang , CHEN Xi , WU Xiao-dong , JIN Sheng. Mixed-coordinated Decision-making Method for Arterial Signals Based on Reinforcement Learning [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(2): 145-153.
[6]	TIAN Hui-juan, LIU Jia-wei, ZHAI Jia-hao, DENG Lin-lin. Video-based Vehicle Speed Measurement Method Using Multiple Intrusion Lines [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 49-56.
[7]	JIA Yan-feng, QU Da-yi, ZHAO Zi-xu, WANG Tao, SONG Hui. Car-following Decision-making and Model for Connected and Autonomous Vehicles Based on Safety Potential Field [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 85-97.
[8]	ZHAO Jian-dong , CHEN Qin , JIAO Yan-li , ZHANG Kai-li , HAN Ming-min. Recognition of Abnormal Driving Behavior of Key Commercial Vehicles [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 282-291.
[9]	XU Dong-wei , PENG Hang , SHANG Xue-tian , WEI Chen-chen , YANG Yan-fang . Road Network Data Repair Based on Graph Autoencoder-generative Adversarial Network [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(6): 33-41.
[10]	YOU Feng , LIANG Jian-zhong , CAO Shui-jin, XIAO Zhi-hao, WU Zhen-jiang , WANG Hai-wei. Dense Pedestrian Crowd Trajectory Extraction and Motion Semantic Information Perception Based on Multi-object Tracking [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(6): 42-54.
[11]	WANG Fu-jian, YU Jia-hao , ZHAO Jin-huan , MEI Zhen-yu. Short-term Public Traffic Passenger Volume Forecasting Method Based on Real-time Relevance of Stations [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(6): 131-144.
[12]	ZHANG Yi , YAO Dan-ya , LI Li , PEI Hua-xin , YAN Song , GE Jing-wei. Technologies and Applications for Intelligent Vehicle-infrastructure Cooperation Systems [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 40-51.
[13]	LONG Jian-cheng, GUO Jia-qi. Review and Prospect of Dynamic Traffic Assignment Research [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 125-138.
[14]	YU Zu-jun, ZHANG Chen-guang , GUO Bao-qing. Vehicle Simultaneous Localization and Mapping Algorithm with Lidar-camera Fusion [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 72-81.
[15]	ZHANG Wei-bin , ZHANG Pu-lin, SU Zi-yi , SUN Feng. Missing Data Repairs for Road Network Traffic Flow with Self-attention Graph Auto-encoder Networks [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(4): 90-98.