Applications of Damped Least-Squares Methods to Resolved-Rate and Resolved-Acceleration Control of Manipulators

1988 ◽  
Vol 110 (1) ◽  
pp. 31-38 ◽  
Author(s):  
C. W. Wampler ◽  
L. J. Leifer
Keyword(s):  
Least Squares ◽  
Rate Of Convergence ◽  
Sensory Feedback ◽  
Inverse Kinematic ◽  
Redundant Manipulators ◽  
Approximate Inverse ◽  
Singular Configurations ◽  
Large Joint ◽  
Resolved Acceleration Control ◽  
Damped Least Squares

Resolved-rate and resolved-acceleration controllers have been proposed for manipulators whose trajectories are determined by real-time sensory feedback. For redundant manipulators, these controllers have been generalized using the pseudoinverse of the manipulator Jacobian. However, near singular configurations, these controllers fail in that they require infeasibly large joint speeds. A damped least-squares reformation of the problem gives approximate inverse kinematic solutions that are free of singularities. Away from singularities the new controllers closely approximate their conventional counterparts; near singular configurations the new controllers remain well-behaved, although the rate of convergence decreases. This paper defines the new controllers and proves their stability. Some aspects of the behavior of the new resolved-rate controller are illustrated in simulations.

Motions With Minimal Joint Torques for Redundant Manipulators

1993 ◽  
Vol 115 (3) ◽  
pp. 599-603 ◽  
Author(s):  
Lee Heow Pueh
Keyword(s):  
Present Method ◽  
Optimization Criterion ◽  
Redundant Manipulators ◽  
Global Level ◽  
Joint Torques ◽  
Optimization Criteria ◽  
Singular Configurations ◽  
Large Joint ◽  
Mechanical Manipulators

The article presents a method for obtaining motions with minimal joint torques for redundant mechanical manipulators. The existing methods based on the local resolution of redundancy do not guarantee that singular configurations, which lead to large joint torques and joint accelerations, will also be avoided while optimizing joint torques. For the present method, the degrees of redundancy are resolved at the global level. It is observed that motions with optimal joint torques are usually associated with large joint speeds and joint accelerations, compared with the joint speeds and joint accelerations for motions with minimal joint speeds or joint accelerations. To overcome this problem, the optimization criterion for minimal joint torques is modified by combining it separately with the optimization criteria for both minimal joint speeds and minimal joint accelerations. The resulting optimal motions, with smaller joint speeds and joint accelerations, are achieved at the expense of having larger joint torques.

An Experimental Study of Resolved Acceleration Control of Robots at Singularities: Damped Least-Squares Approach

1997 ◽  
Vol 119 (1) ◽  
pp. 97-101 ◽  
Author(s):  
M. Kirc´anski ◽  
N. Kirc´anski ◽  
D. Lekovic´ ◽  
M. Vukobratovic´
Keyword(s):  
Least Squares ◽  
Degrees Of Freedom ◽  
Jacobian Matrix ◽  
Control Level ◽  
Singular Values ◽  
Control Scheme ◽  
Resolved Acceleration Control ◽  
Robot Task ◽  
Damped Least Squares ◽  
Value Decomposition

Most of the robot task space control methods based on inverse Jacobian matrix suffer from instability in singular regions of workspace. Methods based on damped least-squares algorithm (DLS) for matrix inversion have been developed but not experimentally confirmed. The application of DLS method at the kinematic control level has been reported in (Chiaverini et al., 1994). In this article, a modified DLS method combined with the resolved-acceleration control scheme, is experimentally verified on two degrees of freedom of a PUMA-560 robot. In order to decrease the position error introduced by the damping, only small singular values are damped, in contrast to the conventional damping method were all the singular values are damped. The symbolic expressions of the singular value decomposition of the Jacobian matrix were used, to decrease the computational burden.

A Factorization of Least-Squares Projection Schemes for Ill-Posed Problems

2020 ◽  
Vol 20 (4) ◽  
pp. 783-798
Author(s):  
Shukai Du ◽  
Nailin Du
Keyword(s):  
Least Squares ◽  
Rate Of Convergence ◽  
Convergence Conditions ◽  
Principal Angles ◽  
Factorization Formula ◽  
Ill Posed

AbstractWe give a factorization formula to least-squares projection schemes, from which new convergence conditions together with formulas estimating the rate of convergence can be derived. We prove that the convergence of the method (including the rate of convergence) can be completely determined by the principal angles between {T^{\dagger}T(X_{n})} and {T^{*}T(X_{n})}, and the principal angles between {X_{n}\cap(\mathcal{N}(T)\cap X_{n})^{\perp}} and {(\mathcal{N}(T)+X_{n})\cap\mathcal{N}(T)^{\perp}}. At the end, we consider several specific cases and examples to further illustrate our theorems.

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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