Abstract
Force sensing plays an irreplaceable role in minimally invasive surgery. Effective force sensing leads to more successful operations by preventing secondary damage to the body. Force feedback is a crucial part of any minimally invasive surgical robotic system. Very compact construction and the challenging disinfection method are challenging in regard to building force sensors into the end of micromanipulator. This paper focuses on clamping force sensing and 2-D touch force sensing for a three-degrees-of-freedom cable-driven micromanipulator. The clamping and touch forces can be detected based on the changes in cable tension. A complete dynamic model of the micromanipulator wrist and driving cable is established. A comprehensive resistance neural network model of the system was obtained through comprehensive resistance tests and data fitting. An external force estimation strategy is proposed based on the changes in driving system resistance. The performance and accuracy of the 2-D force and clamping force estimations were verified experimentally; the results show that the force estimation precision is acceptable. The force-sensing technique discussed here may assist in the future to realize micromanipulator force feedback in minimally invasive surgical robots.
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