Yazar "Majeed, Fatimah Jabbar" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    Estimating Environment Parameters for Teleoperation System with Time Delay
    (IEEE, 2022) Majeed, Fatimah Jabbar; Azeem, Hafiz Huzaifa; Baran, Fray A.
    This paper demonstrates how recursive least squares (RLS) can be used to estimate the parameters of remote environment contact force which can be used to render a virtual environment on the operator side in a bilateral teleoperation system. Proper and fast estimation of the remote environment impedance plays a crucial role in the realization of local force controllers for time delayed teleoperation systems. Addressing that challenge, in this paper, three variants of RLS estimators are implemented and compared against three different impedance models. The algorithms are tested in the simulation environment making use of a recorded real experiment data set. The force reconstruction performances are compared to evaluate the implemented models and estimators. Based on the simulation results, one of the estimators and one of the models are selected for experimental validation on a single degree of freedom motion control system. The results obtained from the experiments confirm how the estimated forces match with that of the actual force responses and provide promising potential for further application in local force controllers of the teleoperation systems.
  • Küçük Resim Yok
    Öğe
    Optimizing soft robot design and tracking with and without evolutionary computation: an intensive survey
    (Cambridge Univ Press, 2024) Stroppa, Fabio; Majeed, Fatimah Jabbar; Batiya, Jana; Baran, Eray; Sarac, Mine
    Soft robotic devices are designed for applications such as exploration, manipulation, search and rescue, medical surgery, rehabilitation, and assistance. Due to their complex kinematics, various and often hard-to-define degrees of freedom, and nonlinear properties of their material, designing and operating these devices can be quite challenging. Using tools such as optimization methods can improve the efficiency of these devices and help roboticists manufacture the robots they need. In this work, we present an extensive and systematic literature search on the optimization methods used for the mechanical design of soft robots, particularly focusing on literature exploiting evolutionary computation (EC). We completed the search in the IEEE, ACM, Springer, SAGE, Elsevier, MDPI, Scholar, and Scopus databases between 2009 and 2024 using the keywords soft robot, design, and optimization. We categorized our findings in terms of the type of soft robot (i.e., bio-inspired, cable-driven, continuum, fluid-driven, gripper, manipulator, modular), its application (exploration, manipulation, surgery), the optimization metrics (topology, force, locomotion, kinematics, sensors, and energy), and the optimization method (categorized as EC or non-EC methods). After providing a road map of our findings in the state of the art, we offer our observations concerning the implementation of the optimization methods and their advantages. We then conclude our paper with suggestions for future research.