异构无人系统协同控制研究进展

Research progress for cooperative control of heterogeneous unmanned systems

  • 摘要: 面对复杂化、多样化和立体化的任务需求,异构无人系统将空、地、海跨域优势互补,最大化提升系统各方面能力,为未来协同作战和智慧民生提供有力的技术保障. 首先,梳理了国内外在跨域协同领域出台的推动性文件,介绍了异构无人系统在军用、科研院所和民用等三方面的实际应用. 其次,针对异构无人系统关键技术之一的协同控制,分别阐述了异构无人系统协同控制在一致性、轨迹跟踪和编队‒合围等三方面的最新进展. 此外,还特别讨论了在不同通信条件下协同控制所面临的挑战和解决方案. 其中,由于一致性和轨迹跟踪存在上层控制理论性和下层控制可行性的区别,进一步从滑模控制、自适应控制、反步控制和自适应动态规划等四方面对轨迹跟踪研究展开阐述. 然后,为了更好地促进异构无人系统协同控制在实际中的应用,通过总结前人相关工作,讨论了其在多约束控制与实时性、多任务切换控制和跨域通信下稳定性等三方面亟需解决的技术瓶颈. 最后,综合异构无人系统协同控制研究现状和实际需求来看,指出了其在深度强化学习与分布式博弈、人机交互以及反群体智能等三方面的发展趋势.

     

    Abstract: Recent advancements in artificial intelligence and control theory have significantly enhanced unmanned systems, endowing them with remarkable capabilities, such as autonomy, self-learning, and scalability. These innovations are pushing unmanned systems toward more distributed and collaborative operational modes. However, the requirements for complex, diverse and stereoscopic missions pose great challenges to unmanned systems. To address such issues, cross-domain collaboration across air, land, and maritime environments using heterogeneous unmanned systems (HUS) offers a promising solution. Such collaboration not only boosts individual system capabilities but also builds a technological foundation for future cooperative operations and smart living scenarios. This paper provides a comprehensive review of the literature on cross-domain collaboration from both domestic and international perspectives. It also discusses the practical engineering applications of HUS in military, scientific research, and civilian fields. Currently, technological progress in this field has been notably spurred by military powers, particularly the United States, the United Kingdom, and France. Although China’s development is still in its nascent stages, it has made significant strides in theoretical and technological research. Research into cross-domain collaboration of HUS involves sophisticated theoretical frameworks and interdisciplinary integration. This paper elaborates on the latest research developments in collaborative control of HUS, focusing on four aspects: consensus, trajectory tracking, formation-containment, and diverse communication scenarios. Given the difference between the theoretical aspects of upper-level control and the feasibility of lower-level control, research on trajectory tracking methods is divided into four main types: sliding mode control, adaptive control, backstepping control, and adaptive dynamic programming. Each control method has its unique strengths, limitations, and suitable scenarios. Despite the rich body of research on cooperative control of HUS, numerous challenges remain in dealing with unknown and complex environments. This paper summarizes previous relevant work and underscores technical challenges across three primary areas: the conflict between multiple constraints and real-time task performance, the issue of multitask switching control, and the problem of maintaining control stability problem under cross-domain communication. Concrete examples are provided to elucidate the difficulties in achieving effective collaborative control for HUS. Based on the current research status and practical requirements for collaborative control of HUS, future development will likely focus on three key areas: deep reinforcement learning and distributed games, human–machine interaction, and antiswarm intelligence. In summary, the broad applicability and strategic importance of collaborative control of HUS have attracted attention from leading military powers, solidifying its status as a pivotal area of technological innovation.

     

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