Priority-based State Machine Synthesis that Relaxes Behavior Design of Multi-arm Manipulators in Dynamic Environments
Priority-based State Machine Synthesis that Relaxes Behavior Design of Multi-arm Manipulators in Dynamic Environments
复制标题
基于优先级的状态机综合，放宽动态环境中多臂机械臂的行为设计
DOI：
10.1080/01691864.2023.2177122
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发表时间：
2023
影响因子：
2
通讯作者：
Yuki Onishi and Mitsuji Sampei
中科院分区：
文献类型：
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作者：
郭 子維;笹山 瑛由;Yuki Onishi and Mitsuji Sampei
本文提出了一个框架，管理多个状态机（SM）产生的运动学耦合多臂机器人的行为。SM是机器人中最常用的控制器切换工具之一，然而，它在某个时间只代表一个运动。这种表征的限制不仅限制了运动学冗余的潜力，而且显著增加了我们在行为设计中必须考虑的情况的数量。为了缓解这一问题，本文提出了一种分布式设计方案和在线综合方法。该框架的基础是基于任务优先级的冗余度机器人控制方法。我们通过引入一个专门用于机器人行为的抽象数据结构来扩展它。抽象的重构与SM自然地联系在一起，从而实现了时序逻辑的并行性。在每个控制回路中构造一个优先级队列，集成为每个效应器设计的SM，该框架自动在线生成全身行为。在动态仿真中，该框架管理四个SM，并实现达到任务与双臂机械手在1 kHz。结果表明，松耦合的SM产生反应性和灵活的决策在动态环境中。
This paper presents a framework governing multiple state machines (SMs) to generate behaviors for kinematically-coupled multi-arm robots. A SM is one of the most used tools to switch controllers in robotics, however, it represents only one motion at a certain time. Such a limit of representation not only restricts the potential of the kinematical redundancy but also significantly increases the number of situations we have to consider in behavior design. To relax the problem, this paper provides a distributed design scheme and an online synthesis method for SMs. The base of the framework is a task-priority-based control method for redundant robots. We expand it by introducing an abstract data structure specialized in robotic behaviors. The abstract reformulation naturally connects with SMs so that the framework realizes parallelism of sequential logic. A priority queue constructed in each control loop integrates SMs designed for each effector, and the framework automatically generates whole-body behaviors online. In dynamic simulations, the framework governs four SMs and achieves reaching tasks with a dual-arm manipulator at 1 kHz. It is shown that the loose coupling of the SMs yields reactive and flexible decisions in a dynamic environment.