A New Weighted Generalized Inverse Algorithm for Pattern Recognition

1977 ◽  
Vol C-26 (10) ◽  
pp. 1009-1017 ◽  
Author(s):  
Al-Alaoui
Keyword(s):  
Pattern Recognition ◽  
Generalized Inverse ◽  
Inverse Algorithm ◽  
Weighted Generalized Inverse

Obstacle Avoidance Algorithm for Redundant Manipulators Based on Weighted Generalized Inverse

2017 ◽  
Vol 872 ◽  
pp. 303-309
Author(s):  
Hai Rui Cao ◽  
Xiao Qin Gu ◽  
Chu Hong Yu
Keyword(s):  
Obstacle Avoidance ◽  
Generalized Inverse ◽  
Redundant Manipulators ◽  
Continuous Transition ◽  
Secondary Tasks ◽  
Field Measuring ◽  
Joint Limits ◽  
The Relationship ◽  
Dangerous Level ◽  
Weighted Generalized Inverse

In this paper, a gradient projection method for redundant robot manipulators based on weighted generalized inverse was presented. By weighting the Jacobian matrix and gradient, not only the obstacles, but also the joint limits could be avoided. In the process of obstacle avoidance, the evaluation function called danger field measuring the dangerous level between the manipulator and obstacles was used and improved. According to the relationship between the value of danger field and the preset threshold, a smooth and continuous transition between the primary and secondary tasks is allowed. This method was proved to be effective by numerical simulations in Matlab.

The Reanalysis Method of Weighted Generalized Inverse for Topological Modification of Plane Structures

2011 ◽  
Vol 138-139 ◽  
pp. 510-515
Author(s):  
Ping Liang ◽  
Jing Wei
Keyword(s):  
Optimal Design ◽  
Stiffness Matrix ◽  
Generalized Inverse ◽  
Inverse Theory ◽  
Topology Change ◽  
Elementary Topology ◽  
Weighted Generalized Inverse

Using a weighed decomposition of the stiffness matrix and the weighed generalized inverse theory, a reanalysis method is presented for the topological modification of plane structures, and a set of formulae of elementary topology change are obtained. These formulae are explicit one and using them one can reanalyze the modified structures in topological optimal design. Finally an example is given to verify the valid of this method.

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