Mechanical Engineering / Makina Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4129
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Article Citation - WoS: 10Citation - Scopus: 10Stiffness Modeling of a 2-Dof Over-Constrained Planar Parallel Mechanism(Elsevier, 2023) Görgülü, İbrahimcan; Dede, Mehmet İsmet Can; Kiper, GökhanStiffness model acquisition of over-constrained parallel mechanisms is relatively difficult since they have more than necessary kinematic loops. In this study, a stiffness modeling solution for over-constrained parallel mechanisms is proposed while considering the computational cost efficiency. Three contributions of the paper are: (1) Presenting the stiffness modeling procedure for serially connected closed-loop structures by using the Virtual Joint Method (2) Considering the effect of dynamic auxiliary forces and dynamic external forces on the mobile platform's deflection and achieving a direct solution by using superposition principle (3) A model fitting procedure for modifying the stiffness coefficients to comply with the experimental data. A 2 degrees-of-freedom over-constrained parallel mechanism is investigated as a case study. However, the proposed stiffness model is 6-DoF since compliant deflections occur in any direction. A finite element analysis and an experimental study verify the model's results.Conference Object Citation - WoS: 3Citation - Scopus: 3Experimental Evaluation of the Success of Peg-In Tasks Learned From Demonstration(IEEE, 2022) Argüz, Serdar Hakan; Ertuğrul, Şeniz; Altun, KeremIndustrial robots are traditionally programmed by hard-coding the desired motion into them. That approach, however, costs significant time and effort and shows little to no promise in transferring human skills to robots. Programming by demonstration (PbD) is an alternative approach that allows robots to learn tasks from demonstrations. Because of its several advantages over the traditional method, PbD is particularly suited for tasks encountered in assembly operations, the most typical of which is the peg-in-hole task. A successful PbD implementation for a peg-in-hole task requires that the peg should still be inserted into the hole even under situations that are not encountered during the demonstrations. Previous research in the field shows that the success rate of a peg-in-hole task under such cases varies greatly. In this study, we use a UR5 manipulator to experimentally investigate how the success rate of a peg-in-hole task changes with respect to the novelty of the task, quantified in terms of the distance of the hole to its original position. It is found that the success ratio decreases as the novelty of the task increases. To increase the performance, the use of strategies that alter the robot's motion dynamically in the run time is suggested for future work.