移动操作规划的时空动作顺序表示*

Yosuke Kawasaki, Masaki Takahashi
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引用次数: 0

摘要

社交机器人被用于根据人类提供的指令执行移动操作任务,例如整理和搬运。基于机器人的子系统配置和物体在环境中的位置,移动操作规划器需要更好地理解机器人在真实空间中的可行动作,从而实现机器人的功能开发。本研究旨在实现一个考虑世界状态的移动操作规划器,世界状态由机器人的状态(子系统配置及其状态)组成,以实现机器人的功能。在本文中,本研究提出了一种新的环境表示,称为世界状态依赖行为图(WDAG)。WDAG采用场景图知识表示和递归多层图结构来表示基于世界状态的可行动作的时空顺序。研究还提出了一种基于WDAG的移动操作规划方法。计划器能够推导出许多有效的动作序列,从而基于对动作的空间和时间联系的详尽理解来完成给定的任务。通过实际的机器实验,对该方法的有效性进行了评价。实验结果表明,该方法有利于机器人功能的有效利用。
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Spatio-Temporal Action Order Representation for Mobile Manipulation Planning*
Social robots are used to perform mobile manipulation tasks, such as tidying up and carrying, based on instructions provided by humans. A mobile manipulation planner, which is used to exploit the robot’s functions, requires a better understanding of the feasible actions in real space based on the robot’s subsystem configuration and the object placement in the environment. This study aims to realize a mobile manipulation planner considering the world state, which consists of the robot state (subsystem configuration and their state) required to exploit the robot’s functions. In this paper, this study proposes a novel environmental representation called a world state-dependent action graph (WDAG). The WDAG represents the spatial and temporal order of feasible actions based on the world state by adopting the knowledge representation with scene graphs and a recursive multilayered graph structure. The study also proposes a mobile manipulation planning method using the WDAG. The planner enables the derivation of many effective action sequences to accomplish the given tasks based on an exhaustive understanding of the spatial and temporal connections of actions. The effectiveness of the proposed method is evaluated through practical machine experiments performed. The experimental result demonstrates that the proposed method facilitates the effective utilization of the robot’s functions.
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