الفهرس 
ACKNOWLEDGMENTOnly 14 pages are availabe for public view
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Abstract
”Soft robotics is a prosperous growing research field that offers innovative designs and ideas that mimic the behavior of natural living beings. Soft robots offer high levels of safety, dexterity, and maneuverability besides being easy to fabricate and actuate. Due to their salient features, soft robots are widely starting to get involved in human oriented applications, especially the minimally invasive surgery. In this thesis, a Transient Finite Element Analysis (TFEA) based methodology is proposed for modeling and developing fiber-reinforced soft robots for minimally invasive surgery (MIS). This proposed methodology can be employed as a generalized theoretical framework for developing of soft robots without the need to fabricate them beforehand. Using the proposed methodology will result in great shortening of the soft robot development cycle. This owes to its capability to be applied for design, optimization, dynamic performance assessment, and controller design. Soft robots are made of rubber-like soft materials that possess highly complex nonlinear behaviors. These behaviors are hyperelasticity, viscoelasticity, and material damage upon loading/unloading cycles. The work presented in this thesis includes cohesive material testing and modeling technique in order to exactly characterize the soft material complex behavior. The soft materials experimental test data are then fitted to different material constitutive laws corresponding to each of the three material behaviors using a combination of ANSYS and Matlab software. Consequently, the parameters of these material constitutive laws can be applied in the ANSYS Workbench environment in order to conduct both static and dynamic simulations. Experimental setup, including a fabricated soft robot prototype, has been carried out so as to validate the TFEA results and confirm its performance and accuracy. Moreover, this work also suggests a lowcost yet practically accurate multi-camera vision tracking system. This vision tracking system is proposed to monitor and register the 3D trajectory of the soft robot. Experimental validation has shown good agreement between the experiments and TFEA results and has proved the TFEA accuracy in predicting the dynamic response of the soft robot. Dynamic modeling is carried out and calibrated using TFEA simulation results. The calibrated dynamic model is used for constructing and optimizing a feedforward inverse optimal PID controller that is then applied for moving the soft robot along any given trajectory.”