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This scheme includes the proposed null space vector being also computed by another properly trained ANN.
The methods all use the null space and associated null vectors of the structural stiffness matrix.
A matrix with a nonzero nonnegative vector in its null space is called central.
These methods are based on the dimensionality of the null space of the equilibrium conditions.
Null space of the Jacobian matrix is studied iteratively, to follow the complete compatibility path.
Further simplifying the matrix puts it in reduced row echelon form R and improves our description of the null space.
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However, the (l_{p} -null space property is difficul_{p} -nullecked for a given matrix.
However, classical null-space compliance laws are defined in joint coordinates, which have some limitations.
The method is based on a new and very simple null-space formulation.
First, an arbitrary desired joint configuration is rarely contained in the robot's null-space, making the desired configuration unattainable.
Moreover, the joint coordinates are not a direct representation of the robot's null-space, which limits its exploitation.
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