2022 Fiscal Year Research-status Report
Automatic Optimal Design of a Visual-based Stiffness Sensor and real-time Colour-coded Stiffness Map for Minimally Invasive Procedures.
| Project/Area Number |
20K14691
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| Research Institution | The University of Tokyo |
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Principal Investigator |
ファラガッソ アンジェラ 東京大学, 大学院工学系研究科(工学部), 特任助教 (80847070)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | Visual-based sensing / Optimal design / MIS / Medical Robotics / Remote Palpation / Stiffness Sensing / Topological Optimization / Real-time Stiffness Map |
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| Outline of Annual Research Achievements |
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.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The research is progressing rather smoothly as the PI is working on the optimization algorithm and in parallel working on the control an planning system which will be integrated with the final design of the sensor.
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| Strategy for Future Research Activity |
In this year the PI will work on the finalization of the optimization algorithm, manufacturing of the sensor and realization of the interface that will be implemented in the clinical room.
Once the optimal design is completed, the sensor will be integrated with the control and planning algorithm of the robot. A real-time stiffness map will be feedback to the remote operator which will be also able to control and replan the motion of the remote-manipulator.
The stiffness information will be used to create and store a colored-code stiffness map.
The integrated system will be tested with phantoms which mimicking the mechanical properties of the humans' anatomical areas.
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| Causes of Carryover |
The PI is planning to purchase an haptic interface that will be placed on the remote site and used by the operator to control the robot. Other expenses are related to the fabrication of the sensor.
Additionally, she will attend to the 2023 IEEE International Conference Robotics and Automation (ICRA) in London where she is co-organizing a forum related to Automation.
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Research Products
(9 results)
