Understanding the principles involved in visually-based coordinated motor control is one of the most fundamental and most intriguing research problems across a number of areas, including psychology, neuroscience, computer vision and robotics. Not very much is known regarding computational functions that the central nervous system performs in order to provide a set of requirements for visually-driven reaching and grasping. Additionally, in spite of several decades of advances in the field, the abilities of humanoids to perform similar tasks are by far modest when needed to operate in unstructured and dynamically changing environments. More specifically, our first focus is understanding the principles involved in human visuomotor coordination. Not many behavioral studies considered visuomotor coordination in natural, unrestricted, head-free movements in complex scenarios such as obstacle avoidance. To fill this gap, we provide an assessment of visuomotor coordination when humans perform prehensile tasks with obstacle avoidance, an issue that has received far less attention. Namely, we quantify the relationships between the gaze and arm-hand systems, so as to inform robotic models, and we investigate how the presence of an obstacle modulates this pattern of correlations. Second, to complement these observations, we provide a robotic model of visuomotor coordination, with and without the presence of obstacles in the workspace. The parameters of the controller are solely estimated by using the human motion capture data from our human study. This controller has a number of interesting properties. It provides an efficient way to control the gaze, arm and hand movements in a stable and coordinated manner. When facing perturbations while reaching and grasping, our controller adapts its behavior almost instantly, while preserving coordination between the gaze, arm, and hand. In the third part of the thesis, we study the neuroscientific literature of the primates. We here stress the view that the cerebellum uses the cortical reference frame representation. The cerebellum by taking into account this representation performs closed-loop programming of multi-joint movements and movement synchronization between the eye-head system, arm and hand. Based on this investigation, we propose a functional architecture of the cerebellar-cortical involvement. We derive a number of improvements of our visuomotor controller for obstacle-free reaching and grasping. Because this model is devised by carefully taking into account the neuroscientific evidence, we are able to provide a number of testable predictions about the functions of the central nervous system in visuomotor coordination. Finally, we tackle the flow of the visuomotor coordination in the direction from the arm-hand system to the visual system. We develop two models of motor-primed attention for humanoid robots. Motor-priming of attention is a mechanism that implements prioritizing of visual processing with respect to motor-relevant parts of the visual field. Recent studies in humans and monkeys have shown that visual attention supporting natural behavior is not exclusively defined in terms of visual saliency in color or texture cues, rather the reachable space and motor plans present the predominant source of this attentional modulation. Here, we show that motor-priming of visual attention can be used to efficiently distribute robot's computational resources devoted to visual processing.
EPFL2015
