A Review on Cooperative Motion Planning of Unmanned Vehicles

被引：0
|
作者：
Kong G. [1 ,2 ]
Feng S. [1 ]
Yu H. [1 ]
Ju Z. [1 ]
Gong J. [1 ]
机构：
[1] School of Mechanical Engineering, Beijing Institute of Technology, Beijing
[2] Unit 32398 of PLA, Beijing
来源：
Binggong Xuebao/Acta Armamentarii | 2023年 / 44卷 / 01期
关键词：
cooperation of multi-agent systems; cooperation of multiple vehicles; motion planning; unmanned vehicles;
D O I：
10.12382/bgxb.2022.0930
中图分类号：
学科分类号：
摘要：
An unmanned ground swarm system consists of multiple unmanned ground mobile platforms, which can achieve common objectives through cooperation and has promising applications in military and transportation systems. Cooperative motion planning is one of the key technologies in the cooperation of unmanned swarm systems or vehicles. It has received increasing attention in both theoretical and application research. This review summarizes and analyzes recent advances in cooperative motion planning of unmanned swarm systems, and provides the background of relevant research. Then the techniques utilized in cooperative motion planning and its applications are briefly discussed considering its development in China and beyond. These techniques are categorized according to different frameworks and algorithms. With such a classification, representative works are discussed regarding their features. Moreover, the challenges and future development of cooperative motion planning are proposed. © 2023 China Ordnance Society. All rights reserved.
引用
收藏
页码：11 / 26
页数：15
相关论文
共 152 条
  • [1] RIZK Y, AWAD M, TUNSTEL E., Cooperative heterogeneous multi-robot systems: a survey, ACM Computing Surveys, 52, 2, pp. 1-31, (2019)
  • [2] CHEN H Y, ZHANG Y., An overview of research on military unmanned ground vehicles, Acta Armamentarii, 35, 10, pp. 1696-1706, (2014)
  • [3] AHMED N, CORTES J, MARTINEZ S., Distributed control and estimation of robotic vehicle networks: overview of the special issue, IEEE Control Systems, 36, 2, pp. 36-40, (2016)
  • [4] ZHAI Z, MARTINEZ ORTEGA J, LUCAS MARTINEZ N, Et al., A mission planning approach for precision farming systems based on multi-objective optimization [J], Sensors, 18, 6, (2018)
  • [5] QIAN D W, XI Y F., Leader-follower formation maneuvers for multi-robot systems via derivative and integral terminal sliding mode[J], Applied sciences, 8, 7, (2018)
  • [6] SCHULZE M, NOCKER G, BOHM K., PReVENT: a european program to improve active safety, Proceedings of the 5th International Conference on Intelligent Transportation Systems Telecommunications, (2015)
  • [7] XU C, QIN H M, WANG J Q., Simply analysis of connected vehicle's role in a partially-connected vehicle group, Proceedings of 2014 International Symposium on Instrumentation and Measurement, Sensor Network and Automation, 4, pp. 1253-1256, (2014)
  • [8] MIGLANI A, KUMAR N., Deep learning models for traffic flow prediction in autonomous vehicles: a review, solutions, and challenges, Vehicular Communications, 20, (2019)
  • [9] TIAN Y, ZHANG K L, LI J Y, Et al., LSTM-based traffic flow prediction with missing data, Neurocomputing, 318, pp. 297-305, (2018)
  • [10] OTTE M, KUHLMAN M J, SOFGE D., Auctions for multi-robot task allocation in communication limited environments, Autonomous Robots, 44, 3, pp. 547-584, (2020)
12345678910