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Thesis
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https://doi.org/10.31428/10317...
Thesis . 2018 . Peer-reviewed
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Una arquitectura neuronal de inspiración biológica para el aprendizaje y control del movimiento de agarre en plataformas robóticas antropomorfas

Authors: Juan López Coronado; Javier Molina Vilaplana;

Una arquitectura neuronal de inspiración biológica para el aprendizaje y control del movimiento de agarre en plataformas robóticas antropomorfas

Abstract

[SPA] En esta Tesis Doctoral se proponen y desarrollan nuevos modelos neuronales de inspiración biológica para el control y aprendizaje de tareas de agarre por parte de dispositivos robóticos antropomorfos. En la primera parte de la Tesis se lleva a cabo una revisión exhausta de los aspectos más relevantes del comportamiento humano y animal durante movimientos de agarre de objetos en la que se resaltan las características invariantes de dicho movimiento, establecidas a través de numerosos experimentos psicofísicos con humanos y primates. A continuación se realiza un repaso al estado actual del conocimiento relativo a la neurobiología que subyace a los comportamientos motrices descritos anteriormente. Con esta base, la Tesis presenta un modelo para la organización del movimiento de agarre que mimetiza las interacciones entre distintas áreas del córtex y los ganglios basales durante la planificación y ejecución del movimiento de agarre en condiciones normales y en condiciones de déficit motor parkinsoniano. El modelo genera trayectorias realistas de agarre a través de la computación y actualización continúa de las señales que codifican la diferencia entre los programas motores que se establecen para la realización de la tarea, y el estado actual de los efectores finales del movimiento involucrados en la ejecución de dicha tarea. Las principales hipótesis del modelo son: (1) el control del transporte de la mano y de la apertura de los dedos se lleva a cabo a través de la acción de señales de paso talámicas cuya modulación corre a cargo de los circuitos neuronales de los ganglios basales. Dichas señales permiten la ejecución coordinada de los distintos subobjetivos que componen una tarea de agarre. (2) La disrupción del programa motriz detectado en la enfermedad de Parkinson, se debe a la modificación en la funcionalidad de la red de interneuronas colinérgicas del estriado ante una deflexión de dopamina estriatal. En estas condiciones, dicha red de interneuronas pierde la habilidad para mantener segregada la información procesada en bucles cortico ganglio basles paralelos y como consecuencia se producen acoplamientos entre distintos canales cortico subcorticales que afectan a los patrones cinemáticos prototípicos del movimiento de agarre. (3) La aplicación de este modelo a un sistema en el que los efectores finales de los movimientos son antropomorficamente realistas, implica el desarrollo, a partir de los resultados de experiencias psicofísicas expresamente diseñadas en esta Tesis Doctoral, de un esquema de control biológicamente plausible para la reducción de la dimensionalidad en el problema de la coordinación del gesto de la mano, durante el movimiento de agarre. Este esquema de control es lo que se define en la Tesis como Biblioteca de Gestos.(4) El aprendizaje que permite el establecimiento de los programas motores tras la percepción del objeto se lleva a cabo a través de una novedosa arquitectura neuronal multi red inspirada en la conectividad cortical entre áreas del córtex parietal posterior y córtex promotor que, tras una serie de etapas de aprendizaje, es capaz de generar movimientos de agarre correctos para un conjunto brazo mano robot antropomorfo cuando a éste sistema se le presentan objetos de distinta forma y tamaño, independientemente de su localización u orientación en el espacio. La Tesis presenta numerosos resultados referentes a la simulación de los modelos en distintas situaciones así como resultados relativos a la implantación de dichos modelos sobre una plataforma robótica antropomorfa orientada al agarre de objetos. Dichos resultados sustentan las hipótesis teóricas que fundamentan esta investigación y por otra parte muestran las capacidades de los modelos desarrollados para actuar como controladores de alto nivel en el guiado de tareas de agarre manipuladores robóticos humanoides.

[ENG] Robotics has become into a traditional field in which research is made by engineers and scientist from different science disciplines such as mathematics, physics, medicine, neurosciences etc. It is evident that in the last years , robotics has evolve to be a multidisciplinary area getting closer and closer to everyday life of human beings such as in the cases of robotics applied to rehabilitation or surgery. It also has been established the use of robotics as a tool for the study of the Man and other biological systems or even to construct artificial anthropomorphic components such as, arms, sensors or cognitive – behavioural schemas able to substitute their biological counterparts in some situations. In the last years, it has been established within the robotics community, the idea about that the understanding of the nervous system of humans and monkeys has also a potential industrial or productive interest. The artificial intelligence industrial devices are more and more inspired in Biology. The brain operates in way very different to the way an actual robot actually operates. The mechanisms for information processing are vastly more complex and subtle in brain neural circuits than in the electronic circuits of the actual robots. The interactions within groups of neurons modify the properties of neural firing of these neurons in their interaction with sensory signals from the external world. An elemental learning such as avoiding behaviours with negative consequences, imply millions of neuronal events, including the reconfiguration and establishment of new neuronal connections. This is what is called ‘adaptability to environment’ of the biological systems. Neuro – Robotics constitutes an emergent and new field which represents, in its objectives, a huge challenge for science ad technology: the transference of fundamental principles of the neurobiology that drives the human behaviour to the diversity of disciplines of the engineering that constitute the Robotics (signal processing, robust and adaptive control, non linear systems, pattern recognition, mechatronics, etc…). If Robotics always has been a multidisciplinary field basically at the technological level, the need to push this field into major advances, requires a stronger interaction between the roboticians and scientist from another fields such as neurosciences, physiology or psychology. The ideas exposed above are the general reference frame in which the work of this PhD Thesis is developed. Concretely, it could be said that, major objectives of this PhD coincide with major objectives of two basic research projects funded by European Commission: BRITE-SYNERAGH (Systems neuroscience and engineering research for anthropomorphic grasping and handling, 1998-2001, BRE-2-CT980797) project and IST/FET-PALOMA (Progressive and adaptive learning for object manipulation: a biologically inspired multi-network architecture, 2001-2004, IST-2001-33073) project. The author of this PhD Thesis is ascribed to NeuroTechnology, Control and Robotics research group of the Universidad Politécnica de Cartagena. This research group and the author of this Thesis, have been intensively involved in the development of the two mentioned European projects.

Programa de doctorado en Tecnologías Industriales. Subprograma Neurotecnología, Control y Robótica

Universidad Politécnica de Cartagena

Country
Spain
Related Organizations
Keywords

Control automático, Grasp movements, Robotic hands, Anthropomorphic manipulators, Applied sciences, Robotics, Movimiento de agarre, Robots, Neural network, Neural networks, Modelos neuronales

15 references, page 1 of 2

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Buessler J. L., Urban J. P., (2003). Modular neural architectures for robotics, Biologically inspired robot behavior engineering, Physica-Verlag GmbH, Heidelberg, Germany.

Bullock, D., Bongers, R., Lankhorst, M., Beek, P. (1999). A vector-integration-toendpoint model for performance of viapoint movements. Neural Networks, 12: 1-29 Bullock, D., Grossberg, S. (1988a). Neural dynamics of planned arm movements: emergent invariants and speed-accuracy trade-offs during trajectory formation.

Psychological Review, 95(1):49 - 90.

Bullock, D., Grossberg, S. (1988b). The VITE model: a neural command circuit for generating arm and articulator trajectories. In J. Kelso, A. Mandell, & M. Shlesinger (Eds), Dynamic patterns in complex systems (pp 206-305). Singapore: World Scientific.

Contreras-Vidal, J.L., Stelmach, G.E. (1995). A neural model of basal gangliathalamocortical relations in normal and parkinsonian movement. Biological Cybernetics, 73(5):467-476. [OpenAIRE]

Graybiel, A.M., Aosaki, T., Kimura, M. (1994). The basal ganglia and adaptive motor control. Science, 265:1826 - 1831 [OpenAIRE]

Graybiel, A.M., Kimura, M. (1995). Adaptive neural networks in the basal ganglia. En J.C. Houk, J.L. Davis & D.G. Beiser (Eds), Models of information processing in the basal ganglia. MIT press (Cambridge, MA), pp. 103 - 116. [OpenAIRE]

Jacobs, R.A., Jordan, M.I., Nowlan, S.J., Hinton, G.E. (1991). Adaptive mixtures of local experts. Neural Computation, 3: 79 - 87.

Levy, R., Hazrati, L.M., Herrero, M.T., Vila, M., Hassani, O.K., Mouroux, M., Ruberg, M., Asensi, H., Agid, Y., Feger, J., Obeso, J.A., Parent, A, Hirsh, E.C. (1996). Re - evaluation of the functional anatomy of the basal ganglia in normal and parkinsonian states. Neuroscience, 76: 335 - 343.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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