A new robotic drive joint friction compensation mechanism using neural networks

Gervini, Vitor Irigon; Gomes, Sebastião Cícero Pinheiro; Rosa, Vagner Santos da

doi:10.1590/s1678-58782003000200004

Cited by 15 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…19 The rigid steel core is elliptical in shape with very small eccentricity. 20 It is surrounded by a flexible race ball bearing. The flexible spline (or flexible) is a thin-walled hollow cup made up of alloy steel.…”

Section: Harmonic Drive Actuatormentioning

confidence: 99%

Design and control of hybrid actuation lower limb exoskeleton

Aguilar-Sierra

Salazar

et al. 2015

Advances in Mechanical Engineering

View full text Add to dashboard Cite

In this article, two types of actuators are applied for a lower limb exoskeleton. They are DC motors with the harmonic drive and the pneumatic artificial muscles. This combination takes advantages of both the harmonic drive and the pneumatic artificial muscle. It provides both high accuracy position control and high ratio of strength and weight. The shortcomings of the two actuators are overcome by the hybrid actuation, for example, low control accuracy and modeling difficult of pneumatic artificial muscle, compactness, and structural flexibility of DC motors. The design and modeling processes are discussed to show the proposed exoskeleton can increase the strength of human lower limbs. Experiments and analysis of the exoskeleton are given to evaluate the effectiveness of the design and modeling.

show abstract

Section: Harmonic Drive Actuatormentioning

confidence: 99%

Design and control of hybrid actuation lower limb exoskeleton

Aguilar-Sierra

Salazar

et al. 2015

Advances in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…A harmonic drive (HD) is compact coaxial gear mechanism characterized by high reduction ratios (up to 300:1), no backlash, and a few number of components, which makes it popular in robotics and automotive applications (De Lucena, Marcelino, & Grandinetti, 2007;Gervini, Gomes, & Da Rosa, 2003). A typical HD consists of three main coaxial components: a circular rigid spline, a flexible spline, and a wave generator (Figure 2).…”

Section: Harmonic Drive Part Consolidationmentioning

confidence: 99%

Part Consolidation for Additive Manufacturing Demonstrated in the Design of a 3D-Printed Harmonic Drive

Cardona

2015

IUJUR

View full text Add to dashboard Cite

The goal of this project is to establish a novel design approach for the additive manufacturing of mechanical transmission systems. Our focus is the design and 3D printing of a harmonic drive. Harmonic drives use the elastic dynamics of metals to create an elliptical rotation, which is what conceives the reduction of speed of the outer piece. Additive manufacturing is used to achieve more complex and precise mechanical structures. Components of less complexity will be 3D printed with polymer and commercial parts will be purchased. There is a need for the creation of new plastics manufacturing processes that define and simplify the decision methods involved in the production. With this project, we will establish the process we consider best for plastic additive manufacturing. The decision of which parts are 3D printed or machined affects the harmonic drive’s cost and lead-time; therefore, several alternatives are systematically analyzed. The final bill of materials contains the list of commercial parts and 3D printed parts. When assembled, a functioning harmonic drive is produced. The final harmonic drive is experimentally tested to determine the life of its components when subjected to working loads. The methods used in this research include the part consolidation for the optimization of the system, transcription of 3D models to STL files that can be printed, polymer additive manufacturing and traditional quality control techniques to improve the design. Material models utilized in this project are commercial aluminum parts, 3D printer and plastic, and a low-voltage power motor. The complete set of results will give torque and speed reduction ratios that will be compared to those previously obtained by electronic simulations. This locates us a step ahead in the creation of an optimal process for additive manufacturing.

show abstract

“…Neurons then produce an output signal by passing the summed input signal through a transfer function (Maqsood et al 2005). Figure 3 shows the neuron architecture used in this study (Gervini et al 2003), which includes a sigmoidal activation function (elaborated below).…”

Section: Artificial Neural Network Modelsmentioning

confidence: 99%

Artificial neural network model for estimating the soil temperature

2011

View full text Add to dashboard Cite

Ozturk, M., Salman, O. and Koc, M. 2011. Artificial neural network model for estimating the soil temperature. Can. J. Soil Sci. 91: 551Á562. Although soil temperature is a critically important agricultural and environmental factor, it is typically monitored with low spatial resolution and, as a result, methods are required to estimate soil temperature at locations remote from monitoring stations. In this study, cost-effective, feed-forward artificial neural network (ANN) models are developed and tested for estimating soil temperature at 5-, 10-, 20-, 50-and 100-cm depths using standard geographical and meteorological data (i.e., altitude, latitude, longitude, month, year, monthly solar radiation, monthly sunshine duration and monthly mean air temperature). These data plus measured monthly mean soil temperature were collected for 2006Á 2008 from 66 monitoring stations distributed throughout Turkey to obtain a total of 2376 data records (36 months)66 monitoring stations) for each of the five soil depths. At each soil depth, 1800 randomly selected data records were used to develop and train a separate ANN model, and the remaining 576 records at each depth were used to test and validate the resulting models. Good agreement was obtained between ANN-estimated soil temperature and measured soil temperature, as evidenced by correlation coefficients of 98.91, 97.99, 99.03, 98.26 and 95.37% for the 5-, 10-, 20-, 50-and 100-cm soil depths, respectively. It was concluded that ANN modeling is a reliable method for predicting monthly mean soil temperature in regions of Turkey where soil temperature monitoring stations are not present.Ozturk, M., Salman, O. et Koc, M. 2011. Un re´seau neuronal artificiel pour estimer la tempe´rature du sol. Can. J. Soil Sci. 91: 551Á562. Malgre´son importance cruciale en tant que facteur agronomique et environnemental, on surveille habituellement la tempe´rature du sol a`une faible re´solution spatiale. Par conse´quent, on a besoin de me´thodes pour estimer la tempe´rature aux endroits e´loigne´s des stations de surveillance. Dans le cadre de cette e´tude, les auteurs ont mis au point puis teste´des mode`les rentables et sans re´troaction fonde´s sur un re´seau neuronal artificiel (RNA) pour estimer la tempe´rature du sol a`5, 10, 20, 50 et 100 cm de profondeur, a`partir des donne´es ge´ographiques et me´te´orologiques usuelles (par ex., altitude, latitude, longitude, mois, anne´e, rayonnement solaire mensuel, dure´e mensuelle de l'ensoleillement et tempe´rature moyenne de l'air mensuelle). Ces donne´es ont e´te´recueillies de 2006 a`2008 avec la tempe´rature moyenne mensuelle du sol dans 66 stations re´parties un peu partout en Turquie, de manie`re a`obtenir 2 376 releve´s (36 mois ) 66 stations de surveillance) pour chacune des cinq profondeurs. À chaque profondeur, on a utilise´800 releve´s, se´lectionne´s au hasard, pour former un mode`le RNA distinct, les 576 autres releve´s servant a`ve´rifier et a`valider les re´sultats. La tempe´rature du sol estime´e graˆce au RNA concorde bien avec ce...

show abstract

A new robotic drive joint friction compensation mechanism using neural networks

Cited by 15 publications

References 0 publications

Design and control of hybrid actuation lower limb exoskeleton

Design and control of hybrid actuation lower limb exoskeleton

Part Consolidation for Additive Manufacturing Demonstrated in the Design of a 3D-Printed Harmonic Drive

Artificial neural network model for estimating the soil temperature

Contact Info

Product

Resources

About