Qualitative physics for robot task planning. I. Grammatical reasoning and commonsense augmentations

Jiming Liu, L. Daneshmend
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引用次数: 1

Abstract

Presents a qualitative reasoning approach to synthesizing robot motion plans from task-level specifications. This method relies on representing the knowledge about robot manipulation as a task grammar augmented with a domain-dependent task analyzer. The task analyzer tests constraints for deriving suboperations pertaining to a higher-level operation and performs commonsense reasoning about the manipulator-level motion strategies. Through several examples, the authors show how syntactical knowledge about robot operations can be formulated for real-world manipulation tasks and how commonsense knowledge can be augmented to constrain the syntactical reasoning.<>
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机器人任务规划的定性物理。1 .语法推理和常识扩充
提出了一种从任务级规范出发综合机器人运动计划的定性推理方法。该方法依赖于将机器人操作知识表示为任务语法,并使用领域相关任务分析器进行扩展。任务分析器测试约束,以派生与高级操作相关的子操作,并执行关于机械手级运动策略的常识性推理。通过几个例子,作者展示了关于机器人操作的语法知识如何为现实世界的操作任务制定,以及如何增强常识知识以约束语法推理。
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