Second-order kinematic control of robot manipulators with Jacobian damped least-squares inverse: theory and experiments

1997 ◽  
Vol 2 (3) ◽  
pp. 188-194 ◽  
Author(s):  
F. Caccavale ◽  
S. Chiaverini ◽  
B. Siciliano
Keyword(s):  
Least Squares ◽  
Robot Manipulators ◽  
Second Order ◽  
Inverse Theory ◽  
Kinematic Control ◽  
Damped Least Squares ◽  
Theory And Experiments

Weighted damped least-squares in kinematic control of robotic manipulators

1992 ◽  
Vol 7 (3) ◽  
pp. 201-218 ◽  
Author(s):  
Stefano Chiaverini ◽  
Olav Egeland ◽  
Rakel K. KANESTROM
Keyword(s):  
Least Squares ◽  
Robotic Manipulators ◽  
Kinematic Control ◽  
Damped Least Squares

scholarly journals Testing the Youth Physical Activity Promotion Model during the COVID-19 Pandemic, with Partial Least Squares Second-Order Latent Constructs

2021 ◽  
Vol 18 (12) ◽  
pp. 6398
Author(s):  
Elena Druică ◽  
Rodica Ianole-Călin ◽  
Monica Sakizlian ◽  
Daniela Aducovschi ◽  
Remus Dumitrescu ◽  
...  
Keyword(s):  
Physical Activity ◽  
Least Squares ◽  
Partial Least Squares ◽  
Online Survey ◽  
Physical Activity Promotion ◽  
Second Order ◽  
Latent Constructs ◽  
Activity Promotion ◽  
Youth Physical Activity ◽  
Mediating Mechanisms

We tested the Youth Physical Activity Promotion (YPAP) framework on Romanian students in order to identify actionable determinants to support participation in physical activity. Our sample consisted of 665 responses to an online survey, with participants aged 18–23 (mean = 19 years); 70% were women. We used the partial least squares algorithm to estimate the relationships between students’ behavior and possible predictors during the COVID-19 pandemic. Our results indicate that all the theoretical dimensions of YPAP (predisposing, enabling and reinforcing) have a positive and significant impact on physical activity, with two mediating mechanisms expressed as predisposing factors: able and worth. Unlike previous research, we used second-order latent constructs, unveiling a particular structure for the enabling dimension that only includes sport competence, fitness and skills, but not the environmental factors.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

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