Molecular conformations from distance matrices
Journal of Computational Chemistry
A Review of data fusion models and architectures: towards engineering guidelines
Neural Computing and Applications
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Localization Algorithms and Strategies for Wireless Sensor Networks
Localization Algorithms and Strategies for Wireless Sensor Networks
A Digital Signal Processing Teaching Methodology Using Concept-Mapping Techniques
IEEE Transactions on Education
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The data obtained from the robotic instrumentation can be redundant due to the multiplicity of sensors. Additionally, the study of the sensor's data can help in optimization the design of the manipulators. In this line of thought, this paper applies two distinct methods for classification of sensors used in robotics. One of the adopted methods leads to arrange the robotic signals in terms of identical spectrum behavior. The other method is the multidimensional scaling technique applied to the correlation of the signals in the time domain. Both methods conduct to similar results, obtaining three groups of signals: the group of "positions", the group of "currents" and the group of "forces, torques and accelerations".