Automatic Optimal Design of a Visual-based Stiffness Sensor and real-time Colour-coded Stiffness Map for Minimally Invasive Procedures.

基于视觉的刚度传感器和实时颜色编码刚度图的自动优化设计，用于微创手术。

基本信息

批准号：
20K14691
负责人：
ファラガッソアンジェラ
金额：
$ 2.66万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Early-Career Scientists
财政年份：
2020
资助国家：
日本
起止时间：
2020-04-01 至 2024-03-31
项目状态：
已结题

项目摘要

The implementation of this research is related to the creation of two systems, one placed in the remote site composed by a robot manipulator and a visual based sensing mechanism, and another placed on the clinical room in which an operator can control and replan the motion of the robot while visualizing real-time stiffness information of the explored anatomical area.A light weight six degree of freedom manipulator, the UFactory Lite6 collaborative robot, has been purchased and interfaced with the Robot Operating System (ROS), a powerful framework which allow implementation of algorithms-simulations for robotics and easy interface with real hardware.A semi-autonomous navigation algorithm, in which the operator can control the motion of the robot remotely and replan the its path, has been implemented using Moveit, a motion planning navigation framework, in ROS.Although the operator can replan the motion of the robot and control it remotely, virtual fixture will be implemented using the visual-stiffness information to control the force and integrate safety futures during the contact.The control and planning algorithm have been initially tested in simulations and are now interfaced with the real robot.A novel 3D machine learning algorithm, that shatters the constraints of conventional methodologies, is implemented to find the optimal design of the sensing mechanism. The method is still in a development phase.

这项研究的实施涉及两个系统的创建，一个系统放置在由机器人操纵器和基于视觉的传感机构组成的远程站点，另一个系统放置在临床室中，操作员可以在其中控制和重新规划机器人的运动。机器人同时可视化所探索的解剖区域的实时刚度信息。已购买轻量级六自由度机械手 UFactory Lite6 协作机器人，并与机器人操作系统 (ROS) 接口，这是一个强大的框架，可实现的机器人技术的算法模拟以及与真实硬件的简单接口。半自主导航算法，其中操作员可以远程控制机器人的运动并重新规划其路径，已使用Moveit（一种运动规划导航框架）实现ROS。虽然操作员可以重新规划机器人的运动并远程控制它，但虚拟夹具将使用视觉刚度信息来实现，以控制接触过程中的力并集成安全未来。控制和规划算法已在模拟，现在与真实机器人交互。采用新颖的 3D 机器学习算法，打破了传统方法的限制，以找到传感机构的最佳设计。该方法仍处于开发阶段。