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Parallel VLSI architectures for real-time kinematics of redundant robots
Author(s) -
Ian D. Walker,
Joseph R. Cavallaro
Publication year - 1994
Publication title -
journal of intelligent and robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.631
H-Index - 77
eISSN - 1573-0409
pISSN - 0921-0296
DOI - 10.1007/bf01258312
Subject(s) - cordic , jacobian matrix and determinant , very large scale integration , inverse kinematics , computer science , kinematics , systolic array , parallel computing , singular value decomposition , computation , digital signal processing , redundancy (engineering) , computer hardware , algorithm , embedded system , field programmable gate array , robot , mathematics , artificial intelligence , classical mechanics , operating system , physics
We describe new architectures for the efficient computation of redundant manipulator kinematics (direct and inverse). By calculating the core of the problem in hardware, we can make full use of the redundancy by implementing more complex self-motion algorithms. A key component of our architecture is the calculation in VLSI hardware of the Singular Value Decomposition of the manipulator Jacobian. Recent advances in VLSI have allowed the mapping of complex algorithms to hardware using systolic arrays with advanced computer arithmetic algorithms. We use CORDIC arithmetic in the novel design of our special-purpose VLSI array, which is used in computation of the Direct Kinematics Solution (DKS), the manipulator Jacobian, as well as the Jacobian Pseudoinverse. Application-specific (subtask-dependent) portions of the inverse kinematics are handled in parallel by a DSP processor which interfaces with the custom hardware and the host machine. The architecture and algorithm development is valid for general redundant manipulators and a wide range of processors currently available and under development commercially.National Science FoundationSandia National Laborator

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