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Optimal design of a spherical parallel manipulator based on kinetostatic performance using evolutionary techniques

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Abstract

This study aims to provide an optimal design for a Spherical parallel manipulator (SPM), namely, the Agile Eye. This aim is approached by investigating kinetostatic performance and workspace and searching for the most promising design. Previously recommended designs are examined to determine whether they provide acceptable kinetostatic performance and workspace. Optimal designs are provided according to different kinetostatic performance indices, especially kinematic sensitivity. The optimization process is launched based on the concept of the genetic algorithm. A single-objective process is implemented in accordance with the guidelines of an evolutionary algorithm called differential evolution. A multi-objective procedure is then provided following the reasoning of the nondominated sorting genetic algorithm-II. This process results in several sets of Pareto points for reconciliation between kinetostatic performance indices and workspace. The concept of numerous kinetostatic performance indices and the results of optimization algorithms are elaborated. The conclusions provide hints on the provided set of designs and their credibility to provide a well-conditioned workspace and acceptable kinetostatic performance for the SPM under study, which can be well extended to other types of SPMs.

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Author information

Authors and Affiliations

  1. iCV Group, Institute of Technology, University of Tartu, Tallinn, Estonia

    Morteza Daneshmand & Gholamreza Anbarjafari

  2. Mechanical Engineering Department, Colorado School of Mines, WashingtonD.C., USA

    Mohammad Hossein Saadatzi

  3. Control and Robotics Laboratory, Department of Automated Production Engineering, École de Technologie Supérieure, Ottawa, Canada

    Mohammad Hadi Farzaneh Kaloorazi

  4. Human-Robot Interaction Laboratory, Faculty of New Sciences and Technologies, University of Tehran, Teheran, Iran

    Mehdi Tale Masouleh

  5. Electrical and Electronic Engineering Department, Hasan Kalyoncu University, Gaziantep, Turkey

    Gholamreza Anbarjafari

Authors
  1. Morteza Daneshmand
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  2. Mohammad Hossein Saadatzi
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  3. Mohammad Hadi Farzaneh Kaloorazi
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  4. Mehdi Tale Masouleh
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  5. Gholamreza Anbarjafari
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Corresponding author

Correspondence to Mehdi Tale Masouleh.

Additional information

Morteza Daneshmand received his B.Sc. in electrical engineering control from Tehran Polytechnic (Amirkabir) University of Technology, Tehran, Iran. His thesis was entitled “Implementation of Distributed Formation Control of Multi-agent Systems on e-puck Mobile Robots”. He received his M.Sc. in mechatronics engineering from the University of Tehran, Tehran, Iran. His thesis was entitled “Kinematic Sensitivity and Workspace Optimization of Planar Parallel Mechanisms”. Since September 2014, he has been a Ph.D. student at the University of Tartu, Tartu, Estonia. He is working on his thesis titled “3D Modeling and Visualization for a Realistic, Virtual Fitting Room”.

Mohammad-Hossein Saadatzi is a Ph.D. student in the Mechanical Engineering Department of Colorado School of Mines. He pursued his undergraduate degree in robotics engineering and his master’s degree in mechatronics engineering in Iran. His academic background and interests are in the interdisciplinary fields of robotics, control, and biomechanics. For his bachelor’s and master’s final projects, he worked on the kinematics, dynamics, design, and control of serial and parallel mechanisms, the results of which have been published in several prestigious journals and conference papers. He also received the IEEE Iran Sections Best MSc Thesis Award in 2012.

Mohammad Hadi Farzaneh Kaloorazi (Hamid Farzane) was born in Rostamabad, Guilan, Iran, in 1988. He received his B.S. degree in electrical engineering from Shahed University, Iran, in 2011. His thesis was entitled “Design and Development of a Remote Control for DC Current Chopper”. He received his M.S. degree in mechatronics from University of Tehran, Iran, in 2014. His thesis was entitled “Workspace Optimization of Parallel Robots, Using Interval Analysis and Geometrical Approach”. He is currently studying as a Ph.D. student in École de Technologie Supérieur, Montreal, Canada. He is working on “Collaborative Automated Fiber Placement (AFP) Manufacturing of Composite Structures”.

Mehdi Tale Masouleh received his B.Eng., M.Sc., and Ph.D. degrees in mechanical engineering (robotics) from Laval University, Québec, Canada, in 2006, 2007, and 2010, respectively. He is currently a faculty member of the Faculty of New Sciences and Technology, University of Tehran. He is also the director of the Human-Robot Interaction Laboratory (known as TaarLab for its Persian abbreviation). His research interests include the kinematics, dynamics, and design of serial and parallel robotic systems as well as humanoids, mobile robots, and optimization techniques (interval analysis and convex optimization, and so on) for robotic applications. He is also the director of a national-level project for a haptic dental simulator.

Gholamreza Anbarjafari received his B.Sc., M.Sc., and Ph.D. degrees from the Department of Electrical and Electronic Engineering, Eastern Mediterranean University, Famagusta, North Cyprus, Turkey, in 2007, 2008, and 2010, respectively. He has been involved in research and projects in the field of image processing and is involved in projects focusing on multimodal emotion recognition, human-robot interaction, super resolution, image compression, watermarking, visualization, and 3D modeling. He is currently working as an Assoc. Prof. in IMS Lab, Institute of Technology, University of Tartu, where he established the iCV research group and is holding the Estonian Research Council Grant.

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Daneshmand, M., Saadatzi, M.H., Kaloorazi, M.H.F. et al. Optimal design of a spherical parallel manipulator based on kinetostatic performance using evolutionary techniques. J Mech Sci Technol 30, 1323–1331 (2016). https://doi.org/10.1007/s12206-016-0239-x

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  • DOI: https://doi.org/10.1007/s12206-016-0239-x

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