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During the last decades, interaction (with humans and with the environment) has become an increasingly interesting topic of research within the field of robotics. At the basis of interaction, a fundamental role is played by the ability to actively regulate the interaction forces. In this paper we propose a technique for controlling the interaction forces exploiting a proximal six axes force/torque...
In this paper we describe the design of a Cartesian Controller for a generic robot manipulator. We address some of the challenges that are typically encountered in the field of humanoid robotics. The solution we propose deals with a large number of degrees of freedom, produce smooth, human-like motion and is able to compute the trajectory on-line. In this paper we support the idea that to produce...
For a complex autonomous robotic system such as a humanoid robot, motor-babbling-based sensorimotor learning is considered an effective method to develop an internal model of the self-body and the environment autonomously. However, learning process requires much time for exploration and computation. In this paper, we propose a method of sensorimotor learning which explores the learning domain actively...
Real autonomous systems are very difficult to design, mainly due to the ever changing conditions of the environments where they are supposed to work. In the area of humanoid robotics these difficulties are increased not only because of the complexity of their mechanical structure, above all because they are supposed to work under the same dynamic conditions as we humans do. Our approach for the creation...
For a complex autonomous robotic system such as a humanoid robot, the learning-based sensory prediction is considered effective to develop a perceptual environment model by itself. We developed a learning system for an autonomous robot to predict the next sensory information from the current sensory information and the expected action. The system we consider contains a learning procedure and a behavior...
The task of tracking an object has been fully studied and many solutions presented before. However, it is a perfect test bed for the study of a novel model using Coupled Chaos Systems. Once an object appears in front of a camera, we demonstrate that the visual input is enough for the self-organization of the torques applied to each of the axes controlling the motion of a simulated eye. No learning...
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