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Realization of task intelligence for service robots in an unstructured environment

机译:在非结构化环境中实现服务机器人的任务智能

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摘要

In order to perform various tasks using a robot in a real environment, it is necessary to learn the tasks based on recognition, to be able to derive a task sequence suitable for the situation, and to be able to generate a behavior adaptively. To deal with this issue, this paper proposes a system for realizing task intelligence having a memory module motivated by human episodic memory, and a task planning module to resolve the current situation. In addition, this paper proposes a technique that can modify demonstrated trajectories according to current robot states and recognized target positions in order to perform the determined task sequence, as well as a technique that can generate the modified trajectory without collisions with surrounding obstacles. The effectiveness and applicability of the task intelligence are demonstrated through experiments with Mybot, a humanoid robot developed in the Robot Intelligence Technology Laboratory at KAIST. (C) 2017 Elsevier Ltd. All rights reserved.
机译:为了在真实环境中使用机器人执行各种任务,必须基于识别来学习任务,以便能够导出适合于该情况的任务序列,并能够自适应地生成行为。为了解决这个问题,本文提出了一种用于实现任务智能的系统,该系统具有由人类情景记忆驱动的存储模块和解决当前情况的任务计划模块。另外,本文提出了一种技术,该技术可以根据当前的机器人状态和识别的目标位置修改演示的轨迹,以执行确定的任务序列,以及一种可以生成修改后的轨迹而不会与周围障碍物发生碰撞的技术。任务智能的有效性和适用性通过在KAIST机器人智能技术实验室开发的人形机器人Mybot的实验得到证明。 (C)2017 Elsevier Ltd.保留所有权利。

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