Abstract: SOM (Self-organizing Maps) model
was introduced to cluster
and analyse on the
human grasping activities of GloveMAPbased on
data reduction of
the initial grasping data. By
acquiring the data reduction of the initial hand grasping data
of the several
objects, it will
be going to be
functioned as the
inputs to the
SOM model. After the
iterative learning of net-trained,
all data of the trained
network will be simulated
and finally self-organized. The
output results of models’ are farthest approached to the
reality in 3-dimensional grasping features.
The experimental result
of the simulation signal will
generate the simulate
result of the
grasping features from the
selected object. The whole experiment of grasping features is
derived into three features / groups and the results are satisfactory.
Keywords: Cluster Analysis, Data reduction, Fingers grasping, Grasping features, SOM neural networks