UBC Theses and Dissertations
High performance optical force sensing - design, characterization and integration in robotic minimally invasive surgery Hadi Hosseinabadi, Amir Hossein
In this thesis, we researched design developments for multi-axis force sensing at the surgeon and the patient consoles of the da Vinci® classic system. A systematic survey on the force sensing literature in Minimally Invasive Surgery (MIS) was conducted. It summarizes the design requirements, compares different technologies, and lists the pros and cons of different locations for sensor integration. While more than 100 articles were published on MIS force sensing, no prior work that addresses force sensing at the surgeon console, without limiting its dexterity, was found. We propose modifications in the wrist’s yaw link of the da Vinci’s Master Tool Manipulator (MTM) for integration of a commercial 6-axis force-torque sensor. The new design does not change the original manipulator’s kinematics and its dexterity. Two example applications of the MTM’s impedance control and joystick control of the Patient Side Manipulator (PSM) were presented to demonstrate the successful integration of the force sensor into the MTM. The mechanical design, electronics hardware, and firmware and software architectures of a novel 6-axis optical force sensor are discussed. The mechatronic design features simple integration, no overload, low-noise, wide dynamic range opto-electronics, and signal conditioning, coupled with co-located digital electronics based on a Field Programmable Gate Array (FPGA) that samples all sensing channels synchronously, enabling very low noise displacement sensing with a resolution of 1.62 nm, low measurement signal latency of 100 μs, high measurement bandwidth of 500 Hz, and high data transfer rates over 11.5 kHz for transmission of six-axis transducer data to a host computer. The transducer’s resolution is better than 0.0001% of the full-scale. The optical force sensor was used for measuring the forces applied to the distal end of a da Vinci® EndoWrist® instrument by mounting it onto its proximal shaft. A new cannula design comprising an inner tube and an outer tube was proposed. A mathematical model of the sensing principle was developed and used for model-based calibration. A data-driven calibration based on a shallow neural network architecture is discussed. The proposed force-sensing requires no modification of the instrument itself; therefore, it is adaptable to different instruments.
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