2020 Fiscal Year Research-status Report
Real-time adaptive control of robots for microsurgery: towards submillimeter accuracy without added sensors
| Project/Area Number |
19K14935
|
|---|
| Research Institution | The University of Tokyo |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2019-04-01 – 2022-03-31
|
| Keywords | 手術ロボット / 適応制御 / 画像処理 / ロボティクス / センサ融合 |
|---|
| Outline of Annual Research Achievements |
The online calibration of surgical instruments using endoscopic images is being investigated.
(1) The method for recognizing and tracking the shaft of surgical instruments on endoscopic images using deep learning was improved. The method was extended to rigid instruments. A preliminary evaluation using real data was performed.
(2) Several versions of the adaptive controller were derived, and a version with proper stability proof has been developed. Preliminary experiments show promise.
(3) A methodology was developed for the generation of realistic CG data based on photorealistic rendering. That development is being used to improve the deep learning algorithms.
(4) The robot programming library DQRobotics has been updated with improved control algorithms and a draft version of the adaptive controller.
|
| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
From April 2020, the adaptive control algorithm has been studied in depth and experimental results have been obtained around September 2020. The algorithm has been further improved and state-of-the-art results have been obtained in March 2021.
Around May 2020, a framework for the generation of synthetic images using a virtual reality simulator was developed. The development of this framework was not initially planned and is a great addition to the project.
During fiscal year 2020, the instrument tracking algorithm has been improved and extended to the estimation of the pose of rigid instruments. It has also been preliminarily validated using real data our February-March 2021.
The DQ Robotics library has been updated, improved, and a draft of the adaptive controller code has been added during fiscal year 2020.
|
| Strategy for Future Research Activity |
The research will continue as originally planned.
- Further improve the instrument tracking algorithm for better accuracy.
- Integrate the instrument tracking algorithm with the adaptive controller.
- Validate the proposed algorithm in experiments using the SmartArm surgical system.
|
| Causes of Carryover |
With the limitation of transit given the ongoing pandemic, the participation in conferences which were originally planned were not feasible in 2020 and might not be feasible in 2021.
Nonetheless, the research itself has progressed in ways not initially planned, and the research will benefit from better computational systems, cameras, and devices in general that can be purchased with this funding.
Moreover, the funding will be used to pay for the publication costs of the currently unpublished results.
|
Research Products
(7 results)
