A Reconfigurable System Approach to the Direct Kinematics of a 5D.o.fRobotic Manipulator
Author(s) -
Diego F. Sánchez,
Daniel M. Muñoz,
Carlos H. Llanos,
José Maurício Santos Torres da Motta
Publication year - 2010
Publication title -
international journal of reconfigurable computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.236
H-Index - 16
eISSN - 1687-7209
pISSN - 1687-7195
DOI - 10.1155/2010/727909
Subject(s) - computer science , field programmable gate array , powerpc , floating point , hardware architecture , hardware acceleration , computer hardware , software , embedded system , fixed point arithmetic , computer engineering , algorithm , programming language
Hardware acceleration in high performance computer systems has a particular interest for many engineering and scientific applications in which a large number of arithmetic operations and transcendental functions must be computed. In this paper a hardware architecture for computing direct kinematics of robot manipulators with 5 degrees of freedom (5 D.o.f) using floating-point arithmetic is presented for 32, 43, and 64 bit-width representations and it is implemented in Field Programmable Gate Arrays (FPGAs). The proposed architecture has been developed using several floating-point libraries for arithmetic and transcendental functions operators, allowing the designer to select (pre-synthesis) a suitable bit-width representation according to the accuracy and dynamic range, as well as the area, elapsed time and power consumption requirements of the application. Synthesis results demonstrate the effectiveness and high performance of the implemented cores on commercial FPGAs. Simulation results have been addressed in order to compute the Mean Square Error (MSE), using the Matlab as statistical estimator, validating the correct behavior of the implemented cores. Additionally, the processing time of the hardware architecture was compared with the same formulation implemented in software, using the PowerPC (FPGA embedded processor), demonstrating that the hardware architecture speeds-up by factor of 1298 the software implementation
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