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Updated: Jul 20, 2026
Design and Fabrication of an Elastomeric Unit for Soft Modular Robots in Minimally Invasive Surgery
Published on: November 14, 2015
Experimental validation of manipulability optimization control of a 7-DoF serial manipulator for robot-assisted
Hang Su1, Andrea Danioni1, Robert Mihai Mira1
1Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano Piazza Leonardo da Vinci, Milano, Italy.
Purpose:
Both safety and accuracy are of vital importance for surgical operation procedures. An efficient way to avoid the singularity of the surgical robot concerning safety issues is to maximize its manipulability in robot-assisted surgery. The goal of this work was to validate a dynamic neural network optimization method for manipulability optimization control of a 7-degree of freedom (DoF) robot in a surgical operation.
Methods:
Three different paths, a circle, a sinusoid and a spiral were chosen to simulate typical surgical tasks. The dynamic neural network-based manipulability optimization control was implemented on a 7-DoF robot manipulator. During the surgical operation procedures, the manipulability of the robot manipulator and the accuracy of the surgical operation are recorded for performance validation.
Results:
By comparison, the dynamic neural network-based manipulability optimization control achieved optimized manipulability but with a loss of the accuracy of trajectory tracking (the global error was 1 mm compare to the 0.5 mm error of non-optimized method).
Conclusions:
The method validated in this work achieved optimized manipulability with a loss of error. Future works should be introduced to improve the accuracy of the surgical operation.
