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Behavior-based manipulator programming based on Extensible Agent Behavior Specification Language

机译:基于可扩展代理行为规范语言的基于行为的机械手编程

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Endowing a robot with skills to perform manipulative tasks has an important role in developing an intelligent robot. To manipulate objects, a robot needs perception and action skills. However, designing the programming framework to integrate a variety of skills in a robot system is a challenging task and significantly influences the robot performance. In this paper, we present a behavior-based manipulator programming framework which is based on Extensible Agent Behavior Specification Language (XABSL) to manage behaviors in a robot system. To achieve the flexibility and reusability of robot behaviors required for practice applications, the proposed concept is to implement a programming framework for robot manipulation into two steps: first, perception and action behaviors are created to endow a robot with fundamental skills to perform manipulative tasks; second, using the XABSL framework, the created behaviors are simply planned by an option graph. Because behaviors are planned to be activated by certain stimuli and respond accordingly, programming robot manipulative tasks becomes simpler. Moreover, by the programming framework for robot manipulative tasks, the programming effort is reduced considerably. In our experiments, we provide an extensive validation of the proposed behavior-based programming framework on the manipulative tasks such as stacking cubes and solving rubik's cube.
机译:使机器人具有执行操纵任务的技能,对开发智能机器人具有重要作用。为了操纵物体,机器人需要感知和动作技巧。但是,设计编程框架以将各种技能集成到机器人系统中是一项艰巨的任务,并且会严重影响机器人的性能。在本文中,我们提出了一个基于行为的机械手编程框架,该框架基于可扩展代理行为规范语言(XABSL)来管理机器人系统中的行为。为了实现实践应用所需的机器人行为的灵活性和可重用性,提出的概念是将机器人操纵的编程框架分为两个步骤:首先,创建感知和动作行为,使机器人具备执行操纵任务的基本技能;其次,使用XABSL框架,可以通过选项图简单地计划创建的行为。由于计划通过特定的刺激来激活行为并做出相应的响应,因此对机器人操纵任务进行编程变得更加简单。此外,通过用于机器人操纵任务的编程框架,可大大减少编程工作量。在我们的实验中,我们对诸如堆叠多维数据集和解决rubik多维数据集之类的操作性任务的拟议的基于行为的编程框架进行了广泛的验证。

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