Estimating Door Shape and Manipulation Model for Daily Assistive Robots Based on the Integration of Visual and Touch Information
Estimating Door Shape and Manipulation Model for Daily Assistive Robots Based on the Integration of Visual and Touch Information
复制标题
基于视觉和触觉信息集成的日常辅助机器人的门形状估计和操纵模型
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. Inaba
中科院分区：
文献类型：
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作者：
Kotaro Nagahama;Keisuke Takeshita;Hiroaki Yaguchi;Kimitoshi Yamazaki;Takashi Yamamoto;M. Inaba
我们提出了一种方法，机器人操纵一个未知的门基于一个单一的用户指令。本文的主要贡献是（i）减少用户的指令，以一个单一的点击和（ii）开发一个有效的方法来估计一个合适的形状和操纵模型的目标门，通过整合视觉和触觉信息获得的机器人。该方法首先使用3-D摄像机检测门候选者，然后根据先前的学习结果估计每个候选者的操作模型。在门的操作过程中，该系统结合视觉和触觉信息来估计形状和操作模型，以生成适当的运动。实验结果证明了该方法的有效性。
We propose a method for a robot to manipulate an unknown door based on a single user instruction. The primary contributions of this paper are (i) to reduce the user instruction to a single click and (ii) to develop an efficient method to estimate an appropriate shape and manipulation model for a target door by integrating visual and touch information obtained by a robot. The proposed method first detects door candidates using a 3-D camera and then estimates the manipulation model of each candidate based on prior learning results. During door manipulation, the system integrates visual and touch information to estimate the shape and manipulation model to generate an appropriate motion. We evaluated the proposed method experimentally, and the results prove that the proposed method is effective.
影响因子：
5
作者：
Sturm, Juergen;Stachniss, Cyrill;Burgard, Wolfram
通讯作者：
Burgard, Wolfram