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Control and Information Process for Multi-Fingers Robot to Acquire Dexterous Grasping and Manipulation

多指机器人获得灵巧抓取和操纵的控制和信息处理

基本信息

批准号：
17360106
负责人：
HAYAKAWA Yoshikazu
金额：
$ 9.86万
依托单位：
Nagoya University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2005
资助国家：
日本
起止时间：
2005 至 2007
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17360106/
关键词：
Dynamics and Control Intelligent Robot ics Machine Learning Modeling Measurement

项目摘要

The results obtained during this project are as follows.1) Control for Stable Grasping and Dexterous ManipulationDynamical constraints on the mechanical system of multi-fingers robot with object depend on how each finger touches to the object: the contact point is fixed or moving with rolling or slipping. By taking those into consideration and from physical view, we were trying to derive a new feedback control low far the stable picking and dexterous manipulation. And also we developed a dynamical model for the multi-fingers robot to grasp an object with contact condition changing, then a lot of knowledge have been obtained on hybrid control of position and force, adaptive control for under-actuated systems, etc.2) Leaning Mechanism for Multi-fingers Robot to Acquire Dexterous SkillIt was shown that non-holonomic Hamiltonian systems can be stabilized by dynamic output feedback, and also it was proven by simulations and experiments that the repetitive control is useful even for non-holonomic Hamiltonian systems. Moreover, the conventional repetitive control was modified to work well in the hybrid control of multi-links systems.3) Estimation Method of Object's Position and Orientation by Sensor IntegrationIn order to control the multi-fingers robot dexterously, accurate information on position of each contact point between each finger and object is needed; thus we established a sensor integration method of force sensors on each finger's tip and two CCD cameras to estimate each finger's contact information and the object's orientation. Moreover, a relation between strain and force of soft-finger tip is modeled in a certain form of nonlinear function and it was verified by experiment that the model works very well.

研究结果如下：1）稳定抓取与灵巧操作控制多指机器人机械系统的动力学约束取决于每个手指与物体的接触方式：接触点是固定的还是滚动或滑动的。在此基础上，从物理的角度出发，提出了一种新的反馈控制方法，使机器人能够实现稳定的拾取和灵巧的操作。建立了多指机器人抓取物体时接触条件变化的动力学模型，在位置和力的混合控制、欠驱动系统的自适应控制等方面取得了一定的成果。2）多指机器人灵巧技能学习的倾斜机构研究表明，非完整Hamilton系统可以通过动态输出反馈镇定，通过仿真和实验证明了重复控制对非完整哈密顿系统也是有效的。3）基于传感器集成的物体位姿估计方法为了实现多指机器人的灵巧控制，需要精确的手指与物体接触点的位置信息;因此，我们建立了一个传感器集成方法的力传感器在每个手指的尖端和两个CCD摄像机估计每个手指的接触信息和对象的方向。此外，还建立了柔性指尖的应变与力之间的非线性函数关系模型，并通过实验验证了该模型的有效性。