首页> 外文会议>2018 IEEE International Work Conference on Bioinspired Intelligence >Smart Placement of a Two-Arm Assembly for An Everyday Object Manipulation Humanoid Robot Based on Capability Maps
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Smart Placement of a Two-Arm Assembly for An Everyday Object Manipulation Humanoid Robot Based on Capability Maps

机译:基于功能图的日常对象操纵人形机器人两臂组件的智能放置

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摘要

A robot that will execute everyday object manipulation tasks needs a competent body that can handle as many different objects as possible in as many ways as possible. To accomplish this, we must design the robot body in such a way that will allow it to achieve many different ways to manipulate the objects. In this work, we present a design method to mount a two-arm assembly in a torso and a mobile base (to complete a humanoid robot) taking into account a voxelized structure of points to reach and a variable orientation and relative position of both arms. We make use of the concept of capability maps to calculate a score for different possible two-arm assembly placements. An object to manipulate is selected. In particular, we are using the object size as the most important manipulation feature. We test many possible arm mounting configurations with many different object positions and we run an object reaching simulation for each of these combinations. The successfulness of each of these trails is used to derive a capability map. A score for each map (that corresponds to a different arm mounting configuration) is derived and used to select the final placement of the robot. With this work, we present an effective process to determine the best arms bases placement accord to the collaborative reaching results for a two-arm humanoid robot.
机译:能够执行日常对象操作任务的机器人需要一个能胜任的机构,能够以尽可能多的方式处理尽可能多的不同对象。为此,我们必须以这样一种方式设计机器人主体,使其能够实现许多不同的方式来操纵对象。在这项工作中,我们考虑到要到达的点的体素化结构以及两个手臂的可变方向和相对位置,提出了一种将两臂组件安装在躯干和活动基座上的设计方法(以完成人形机器人) 。我们利用功能图的概念来计算不同的两臂装配位置的得分。选择要操作的对象。特别是,我们将对象大小用作最重要的操作功能。我们用许多不同的对象位置测试了许多可能的手臂安装配置,并针对这些组合中的每一个运行了一个达到模拟的对象。这些路径中的每条路径的成功度都用于导出功能图。得出每个地图的分数(对应于不同的手臂安装配置),并将其用于选择机器人的最终放置位置。通过这项工作,我们提出了一个有效的过程,以确定与两臂人形机器人的协作到达结果相符的最佳武器库位置。

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