FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

Carlos Rodriguez-Donate,Luis Morales-Velazquez,Gilberto Herrera-Ruiz,Roque Alfredo Osornio-Rios,Rene De Jesus Romero-Troncoso

doi:10.3390/s100404114

Carlos Rodriguez-Donate, Luis Morales-Velazquez + Show 3 more

Open Access

https://doi.org/10.3390/s100404114

Copy DOI

Abstract

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA).

Highlights

Intelligent robotics, as defined by Lopez-Juarez, et al [1], demands the integration of smart sensors [2,3] that allow the controller to efficiently measure physical quantities
This work proposes a new smart sensor to simultaneously obtain several parameters related to motion dynamics and inclination, along with the separation of the vibration information using two primary sensors: an encoder and a triaxial accelerometer on a single link of industrial robots
Results on motion dynamics and inclination estimations show the effectiveness of this smart sensor that integrates data fusion among primary sensor data

Summary

Introduction

Intelligent robotics, as defined by Lopez-Juarez, et al [1], demands the integration of smart sensors [2,3] that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require constant monitoring of several variables and their fusion [4,5,6] such as: motion dynamics, inclination, and vibration; these variables inform about the machine wellness, highlighting the necessity of a specialized smart sensor that provides sufficient information to evaluate the robot performance. In the case of using finite differentiation, quantization noise overwhelms the signal, making some filtering necessary This differentiation and filtering stage can be performed by a combination of an averaging decimation filter [22], a finite difference stage, and a linear interpolation stage to estimate motion dynamic parameters (p, v, a, and j) as shown, 1j, 1k, and 1l This differentiation and filtering stage can be performed by a combination of an averaging decimation filter [22], a finite difference stage, and a linear interpolation stage to estimate motion dynamic parameters (p, v, a, and j) as shown in Figure 1i, 1j, 1k, and 1l

Methods

Results

Discussion

Conclusion