A next-best-view algorithm for autonomous 3D object modeling by a humanoid robot

A next-best-view algorithm for autonomous 3D object modeling by a humanoid robot
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用于人形机器人自主 3D 对象建模的次佳视图算法

DOI:
10.1109/ichr.2008.4756001
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发表时间:
2008
期刊:
Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots
影响因子:
--
通讯作者:
A. Kheddar
A. Kheddar
中科院分区:
--
文献类型:
--
作者:
T. Foissotte;O. Stasse;Adrien Escande;A. Kheddar

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我们提出了我们的研究,使人形机器人自主建立未知物体的几何模型。虽然已经提出了良好的方法,在建模和识别过程中的下一个最佳视图的具体问题,我们的方法是不同的,并考虑到嵌入式视觉传感器和冗余运动能力方面的人形特异性。在每个建模步骤中选择最佳下一个感兴趣的视图的问题被制定为一个优化问题,其中整个机器人的姿态需要与机器人cameraspsila位置和方向共同定义。为了实现这一点,我们提出了一个可微公式,表示从特定的角度来看,可见的未知数据的量,只给在前面的步骤中获得的知识。此外,引入了一个特定的稳定性约束,以允许机器人达到一个配置,它的脚可以移动远离他们的初始位置。
We present our investigation to make humanoids build autonomously geometric models of unknown objects. Although good methods have been proposed for the specific problem of the next-best-view during the modeling and the recognition process; our approach is different and takes into account humanoid specificities in terms of embedded vision sensor and redundant motion capabilities. The problem to select the best next view of interest at each modeling step is formulated as an optimization problem where the whole robot posture needs to be defined jointly with the robot cameraspsila position and orientation. To achieve this, we propose a differentiable formula that expresses the amount of unknown data visible from a specific viewpoint, given only knowledge acquired in previous steps. In addition, a specific stability constraint is introduced to allow the robot to reach a configuration where its feet can be moved away from their initial position.
使用人形机器人进行在线物体搜索
DOI: --
发表时间: 2007
期刊:
影响因子: --
作者:
Francois Saidi;Olivier Stasse;Kazuhito Yokoi;and Fumio Kanehiro
通讯作者: and Fumio Kanehiro