摘要:自主机器人是一类由计算机软件控制的信息物理系统，如何支持该类机器人在开放环境下的有效和协调运行，是自主机器人控制软件（control software of autonomous robot，简称CSAR）研究与实践面临的一项重要挑战.基于组织理论的思想，采用Structure-in-5的组织架构模式，提出了基于多智能体的CSAR的软件架构MaRSA（multi-agent robotic software architecture），通过独立抽象CSAR的行为规划、分发、执行等软构件，并显式加强这些构件间的交互，从而为自主机器人行为的有效规划和协调实施奠定架构基础；提出了基于MaRSA架构的伴随行为机制，从因果性、时序性和按需性等3个方面建立了机器人观察行为和任务行为间的伴随关系，并基于分步规划和动态决策的思想，设计并实现了伴随行为的自主决策算法DAAB（decision algorithm of accompanying behaviors）.分别在仿真环境和实际机器人环境下设计了对比性实验，结果表明：与主流的反应式行为决策算法和BDI式概率决策算法相比较，基于MaRSA和伴随行为机制的DAAB算法所生成的伴随行为规划在开放环境下具有可行性和更高效的执行效率.



Abstract:Autonomous robot is a kind of complex cyber-physical system controlled by software. To support robots to operate in open environment in an effective and cooperative way is a great challenge for the researches and practices of control software of autonomous robot (CSAR). Adopting organization theory, this paper presents a multi-agent software architecture MaRSA (multi-agent robotic software architecture) that takes structure-in-5 organization style for CSAR. The software components of plan, dispatch, and execute behaviors of robot are independently encapsulated and explicitly separated, which lays architecture foundation for the flexible cooperation and continuous interactions among these components. The paper further proposes an accompanying behavior mechanism to enrich the interactions of observation actions and task actions, defines three kinds of accompanying relationships on the causality, temporal, and on-demand viewpoints, as well as designs a two-step dynamic decision algorithm DAAB (decision algorithm of accompanying behaviors) for planning accompanying behaviors. Two experiments are conducted in simulation robot environment and the real robot environment respectively, and the results show that comparing with the reactive behavior planning algorithm and BDI-based probabilistic planning algorithm, the proposed algorithm DAAB can produce plans that operate in open environment with high efficiency and low efforts to accomplish tasks.



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