多机协同自主任务规划系统研究综述
Review of multi-UAV collaborative autonomous task planning systems
柴蓉 1杨泞渝 1段晓芳 1艾新雨 1陈前斌1
作者信息
- 1. 重庆邮电大学 通信与信息工程学院,重庆 400065;重庆市移动通信技术重点实验室,重庆 400065
- 折叠
摘要
针对多机协同自主任务规划显著提升无人机任务感知效能、提高任务执行能力的现状,对其关键技术进行阐述,主要包括知识表示、通感一体化、任务调度及航迹规划等技术.针对知识表示技术,阐述基于任务环境上下文感知的知识库构建方法,进而对多域融合知识图谱构建、动态知识图谱更新与共享方法进行分析总结;针对通感一体化技术,分析了环境适变、灵活可扩的多机协同通感一体化架构,进而揭示多机协同通感一体化理论能限,阐述面向任务差异性需求的资源共享方法;针对任务调度及航迹规划技术,阐述资源适配的多机协同自主任务调度方案,并对基于动力学模型的航迹控制策略及不完美环境下的鲁棒控制机制进行分析总结.
Abstract
Collaborative autonomous task planning of multiple unmanned aerial vehicles(UAVs)is expected to significant-ly enhance task perception efficiency and execution performance.In this paper,an overview of the key technologies in col-laborative autonomous task planning systems of multiple UAVs is presented,including knowledge representation methods,the integrated sensing and communication technology,and the task scheduling and trajectory planning technology of the UA-Vs.Regarding knowledge representation methods,a context-aware knowledge base construction method is proposed,and a multi-domain fusion knowledge graph and dynamic knowledge graph updating and sharing methods are summarized.For the integrated sensing and communication technology in multi-UAV collaborative task execution scenarios,an environment-a-daptive and flexible scalable multi-UAV collaborative sensing and communication integration framework is proposed,the theoretical performance limitations of collaborative sensing and communication integration are analyzed,and resource sha-ring methods tailored to varying task demands are presented.Regarding the task scheduling and trajectory planning problem in multi-UAV collaborative task execution scenarios,a resource-adaptive multi-UAV collaborative autonomous task schedu-ling scheme is presented,then a dynamic model-based multi-UAV collaborative autonomous trajectory control strategy is discussed.Finally,a robust control mechanism in imperfect multi-UAV collaborative environment is proposed.
关键词
无人机/知识表示/协同任务感知/通感一体化/任务规划Key words
unmanned aerial vehicles/knowledge representation/collaborative task perception/integrated sensing and com-munication/task planning引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据