Automatic aid for robot control system design

Xingyun He, Lei Shi
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Abstract

With the rapid advancements in robotic technologies, the increasing diversity of hardware and software in robot systems has a significant impact on the design of robot control systems. The structure of robots becomes more and more sophisticated with the growing of the number of receptors and effectors. Integrating receptors and effectors to agents in multi-agent robotic system in order to complete a set of tasks is an important problem demanding efficient solution in the robot control system design. We present a bin-packing algorithm for task allocation and a graph nodes consolidation approach for resource allocation. Our bin-packing algorithm can allocate the tasks to each agent to meet the constraints of the computational ability of agents and the execution time of tasks, while guaranteeing all tasks can be completed. The graph nodes consolidation algorithm allocates all the resources to agents while minimizing the number of connections between agents, leading to a communication-efficient system structure. The proposed algorithms have polynomial time complexity compared with constrained guess-check and brutal force methods for solving complex multi-agent resource allocation problems.
自动辅助机器人控制系统的设计
随着机器人技术的飞速发展,机器人系统中硬件和软件的日益多样化对机器人控制系统的设计产生了重大影响。随着受体和效应器数量的增加,机器人的结构也越来越复杂。在多智能体机器人系统中,如何将感受器、效应器与智能体结合起来完成一系列任务是机器人控制系统设计中需要有效解决的一个重要问题。提出了一种任务分配的装箱算法和一种资源分配的图节点整合方法。我们的装箱算法可以在保证所有任务都能完成的前提下,将任务分配给每个agent,以满足agent计算能力和任务执行时间的约束。图节点整合算法将所有资源分配给代理,同时最大限度地减少了代理之间的连接数量,从而实现了高效通信的系统结构。在求解复杂的多智能体资源分配问题时,与约束猜测检查和野蛮力方法相比,该算法具有多项式时间复杂度。
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