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A Novel Framework for Closed-Loop Robotic Motion Simulation Part I: Inverse Kinematics Design

MPS-Authors
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Robuffo Giordano,  P
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Tesch,  J
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Breidt,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Cognitive Engineering, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Robuffo Giordano, P., Masone, C., Tesch, J., Breidt, M., Pollini, L., & Bülthoff, H. (2010). A Novel Framework for Closed-Loop Robotic Motion Simulation Part I: Inverse Kinematics Design. In 2010 IEEE International Conference on Robotics and Automation (ICRA 2010) (pp. 3876-3883). Piscataway, NJ, USA: IEEE.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-C036-D
Abstract
This paper considers the problem of realizing a 6-DOF closed-loop motion simulator by exploiting an anthropomorphic serial manipulator as motion platform. Contrary to standard Stewart platforms, an industrial anthropomorphic manipulator offers a considerably larger motion envelope and higher dexterity that let envisage it as a viable and superior alternative. Our work is divided in two papers. In this Part I, we discuss the main challenges in adopting a serial manipulator as motion platform, and thoroughly analyze one key issue: the design of a suitable inverse kinematics scheme for online motion reproduction. Simulation results are proposed to analyze the effectiveness of our approach. Part II will address the design of a motion cueing algorithm tailored to the robot kinematics, and will provide an experimental evaluation on the chosen scenario: closed-loop simulation of a Formula 1 racing car.