Universidad Politécnica de Cartagena TESIS DOCTORAL “UNA ...

The results of the research developed in this PhD Thesis could be applied in areas
in which a human – like behaviour could be needed for the robot operation, such as
advanced prosthetics, service robotics or rehabilitation robotics.
3. Organization of the Thesis
This Thesis has been organized in the following way: in Chapter 1, we describe the
more relevant aspects related with animal and human motor behavior during reach to
grasp tasks. We review the invariant properties of the reach to grasp movement,
defined by a number of experiences with humans and primates. This Chapter also
reviews the actual knowledge about the subjacent neurobiology related with the
organization of the prehension movement.
In Chapter 2, we review the computational models present in the bibliography that
have tried to explain the phenomenology (or part of it) related with the reach to grasp
movement (Haggard and Wing model, Hoff – Arbib model, Ulloa-Bullock model,
Smeets – Brenner, model). After this review is completed, we present a computational
neural model for the coordination of the reach to grasp movement. Simulation of the
model under different situations are presented and we obtain the operational properties
of the system by comparing these results with the results of similar experiences carried
out by humans. We also discuss the emergent properties (the properties that are not
explicitly taken into account during the design phase) of the model. Finally the results
of the simulation of our model are compared with the results offered by the models
named above.
In Chapter 3 we study the phenomenology associated to Parkinson’s disease in
reach to grasp movements. This review of phenomena provides the start point for the
development of a new computational neural model able to explain the properties of the
kinematic patterns of the reach to grasp movement in Normal and Parkinsonian states.
We use techniques of computational neuroscience to develop models that constitute a
plausible neural representation of the referred spatio-temporal patterns associated to
the different components of the prehension movement. We use the Parkinsonian state
as a window to test and validate the hypothesis that have lead to the models presented
in this Chapter and in the previous Chapter.
In Chapter 4, we began with the process of trying to transfer some neurobiological
principles to the design of new robotic hand controllers. This process consists in to put
the models presented in previous Chapters in a form suitable to act as advanced robotic
controllers that can be implanted easily on an anthropomorphic robot. In this Chapter, a