A Robotic System with a Hybrid Motion Cueing Controller for Inertia Tensor Approximation in Micro-Manipulations
Author(s) -
Umar Asif,
Javaid Iqbal
Publication year - 2011
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/45702
Subject(s) - computer science , kinematics , inertia , actuator , control theory (sociology) , controller (irrigation) , tensor (intrinsic definition) , moment of inertia , motion (physics) , motion control , simulation , control engineering , artificial intelligence , robot , mathematics , physics , control (management) , classical mechanics , engineering , pure mathematics , agronomy , biology
This paper summarizes the development of a robotic system for the approximation of inertia tensor of micro-sized rigid bodies. We described the design and computer-based simulation of a 6-DOF motion platform in our earlier work [32] that benefits from an anthropological serial manipulator design. In [32] we emphasized that, in contrast to a standard configuration based on linear actuators, a mechanism with actuator design inspired from an anthropological kinematic structure offers relatively a larger motion envelope and higher dexterity making it a viable motion platform for micromanipulations. After having described the basic design and kinematic analysis of our motion platform in [32], we now aim to propose an advanced motion cueing algorithm for facilitating the identification of inertial parameters at micron-level. The motion cueing algorithm for achieving high fidelity dynamic simulation is described in this paper using a hybrid force-position-based controller. The inertia tensor identification is done by generating a controlled motion on the specimen and measuring the resultant forces and moments to approximate the inertia tensor using rigid body dynamics equations. The paper evaluates the performance of the controller using closed-loop dynamic simulations and validates the significance of the proposed method through experimental results
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