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Li L, Li X, Ouyang B, Mo H, Ren H, Yang S. Three-Dimensional Collision Avoidance Method for Robot-Assisted Minimally Invasive Surgery. CYBORG AND BIONIC SYSTEMS 2023; 4:0042. [PMID: 37675200 PMCID: PMC10479965 DOI: 10.34133/cbsystems.0042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 07/27/2023] [Indexed: 09/08/2023] Open
Abstract
In the robot-assisted minimally invasive surgery, if a collision occurs, the robot system program could be damaged, and normal tissues could be injured. To avoid collisions during surgery, a 3-dimensional collision avoidance method is proposed in this paper. The proposed method is predicated on the design of 3 strategic vectors: the collision-with-instrument-avoidance (CI) vector, the collision-with-tissues-avoidance (CT) vector, and the constrained-control (CC) vector. The CI vector demarcates 3 specific directions to forestall collision among the surgical instruments. The CT vector, on the other hand, comprises 2 components tailored to prevent inadvertent contact between the robot-controlled instrument and nontarget tissues. Meanwhile, the CC vector is introduced to guide the endpoint of the robot-controlled instrument toward the desired position, ensuring precision in its movements, in alignment with the surgical goals. Simulation results verify the proposed collision avoidance method for robot-assisted minimally invasive surgery. The code and data are available at https://github.com/cynerelee/collision-avoidance.
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Affiliation(s)
- Ling Li
- School of Management, Hefei University of Technology, Hefei, China
- Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education), Hefei University of Technology, Hefei, China
- Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance (Ministry of Education), Hefei University of Technology, Hefei, China
| | - Xiaojian Li
- School of Management, Hefei University of Technology, Hefei, China
- Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education), Hefei University of Technology, Hefei, China
- Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance (Ministry of Education), Hefei University of Technology, Hefei, China
| | - Bo Ouyang
- School of Management, Hefei University of Technology, Hefei, China
- Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education), Hefei University of Technology, Hefei, China
- Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance (Ministry of Education), Hefei University of Technology, Hefei, China
| | - Hangjie Mo
- School of Management, Hefei University of Technology, Hefei, China
- Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education), Hefei University of Technology, Hefei, China
- Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance (Ministry of Education), Hefei University of Technology, Hefei, China
- Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance (Ministry of Education), Hefei University of Technology, Hefei, China
| | - Hongliang Ren
- Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore, Singapore
- Department of Electronic Engineering, Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Shanlin Yang
- School of Management, Hefei University of Technology, Hefei, China
- Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance (Ministry of Education), Hefei University of Technology, Hefei, China
- National Engineering Laboratory for Big Data Distribution and Exchange Technologies, Shanghai, China
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Ma X, Song C, Chiu PW, Li Z. Visual Servo of a 6-DOF Robotic Stereo Flexible Endoscope Based on da Vinci Research Kit (dVRK) System. IEEE Robot Autom Lett 2020. [DOI: 10.1109/lra.2020.2965863] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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