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首页> 外文期刊>IEEE transactions on systems, man, and cybernetics. Part B >Task planning for a mobile robot in an indoor environment using object-oriented domain information
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Task planning for a mobile robot in an indoor environment using object-oriented domain information

机译:使用面向对象的域信息在室内环境中进行移动机器人的任务计划

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摘要

For a mobile robot to be practical, it needs to navigate in dynamically changing environments and manipulate objects in the environment with operating ease. The main challenges to satisfying these requirements in mobile robot research include the collection of robot environment information, storage and organization of this information, and fast task planning based on available information. Conventional approaches to these problems are far from satisfactory due to their requirement of high computation time. In this paper, we specifically address the problems of storage and organization of the environment information and fast task planning in the area of robotic research. We propose an special object-oriented data model (OODM) for information storage and management in order to solve the first problem. This model explicitly represents domain knowledge and abstracts a global perspective about the robot's dynamically changing environment. To solve the second problem, we introduce a fast task planning algorithm that fully uses domain knowledge related to robot applications and to the given environment. Our OODM based task planning method presents a general frame work and representation, into which domain specific information, domain decomposition methods and specific path planners can be tailored for different task planning problems. This method unifies and integrates the salient features from various areas such as database, artificial intelligence, and robot path planning, thus increasing the planning speed significantly.
机译:为了使移动机器人切实可行,它需要在动态变化的环境中导航并轻松操作环境中的对象。在移动机器人研究中满足这些要求的主要挑战包括机器人环境信息的收集,该信息的存储和组织以及基于可用信息的快速任务计划。由于需要大量的计算时间,因此解决这些问题的常规方法远不能令人满意。在本文中,我们专门解决了机器人研究领域中环境信息的存储和组织以及快速任务计划的问题。为了解决第一个问题,我们提出了一种用于信息存储和管理的特殊的面向对象的数据模型(OODM)。该模型明确表示领域知识,并抽象出有关机器人动态变化环境的全局视图。为了解决第二个问题,我们引入了一种快速的任务计划算法,该算法充分利用了与机器人应用程序和给定环境相关的领域知识。我们基于OODM的任务计划方法呈现了一般的框架和表示形式,可以针对不同的任务计划问题量身定制域特定的信息,域分解方法和特定的路径规划器。该方法统一并集成了数据库,人工智能和机器人路径规划等各个领域的显着特征,从而显着提高了规划速度。

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