Siamak Arbatani

Micro-optical force distribution sensing suitable for lump/artery detection.

Surgeons performing robotic-assisted surgical tasks need to establish the density and constituency of hidden tissue structures using only surgical tools. This is possible by integrating a miniaturized sensor into the end-effectors of robotic surgical systems. In this present work, optical microsystems technology is utilized to develop a miniature force-distribution sensor that can be integrated into surgical end-effectors. The sensing principle of the sensor is based on the mechanism of splice coupling. Since the device is fully optical, the sensor is magnetic-resonance compatible and is also electrically passive. The experimental results performed on the developed sensor confirm its ability to measure the distributed force information. Such information is used to detect different tissue structures such as lumps, arteries, or ureters during robotic-assisted surgical tasks.

Real-Time Parameter Identification of Hyperelastic Materials in a Closed Loop System Using Tactile Feedback

Real time identification of materials with nonlinear characteristics is a challenging task. One of the characteristic which is very challenging to model is the stress relaxation behavior, which results in nonlinearity in mechanical behavior of material. A novel method is proposed in this research for real-time identification of materials possessing this behavior during Telemanipulation using Fuzzy logic algorithm. The proposed algorithm is evaluated in an experimental setup consisting a five degrees of freedom serial manipulator (Catalyst-5T) equipped with a strain-gauge sensor with a ball-caster tip. The system is able to detect surface of the material, then perform the identification task by implementing a specified depth of indentation on material and sliding horizontally on surface of the material while maintaining the applied indentation depth. Based on the real time data of stress relaxation time and measured force of indentation as inputs of Fuzzy material identification algorithm, material type is identified in real-time. Output of the system is crisp value which indicates the material type. Proposed algorithm is validated in a designed experimental scenario which consists of three different materials. Experimental results confirm reliability and precision of the proposed algorithm in material type discrimination.