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Smart surgical control under RCM constraint using bio-inspired network
- Source :
- Neurocomputing. 470:121-129
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- In this paper, we propose a control framework for intelligent surgical robots under the Remote Center of Motion (RCM). The goal of a surgical robot is to assist surgeons in performing complex surgeries. RCM constraint implies that the surgical tip attached to the end-effector of the surgical robot does not slide away from the point of the incision while performing surgery. Implementation of a control algorithm to comply with RCM constraints is a complicated task because of the nonlinear model of the surgical robots and stringent conditions of accuracy imposed by the patient’s safety. This paper proposes an optimization-driven approach to perform the surgical maneuver under RCM constraints. We then applied a bio-inspired optimization algorithm to solve the problem efficiently. For testing the performance of ZNNBAS, we used MATLAB to simulate a surgical procedure. A 7-DOF surgical robot (KUKA LBR IIWA 7) was used as a test bench for running the simulations. The simulation results show that the ZNNBAS is comparable with BAS, PSO, and GA and efficiently and robustly performed the task commanded maneuvers while enforcing the RCM constraints.
- Subjects :
- Test bench
ComputingMethodologies_SIMULATIONANDMODELING
Computer science
Cognitive Neuroscience
Control (management)
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Computer Science Applications
Task (project management)
Constraint (information theory)
Artificial Intelligence
Nonlinear model
Point (geometry)
MATLAB
computer
Surgical robot
Simulation
ComputingMethodologies_COMPUTERGRAPHICS
computer.programming_language
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 470
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi.dedup.....01efbbf62e4ad573ef5f90dd35c9ea72