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We present an integrated approach allowing the humanoid robot iCub to learn the skill of archery. After being instructed how to hold the bow and release the arrow, the robot learns by itself to shoot the arrow in such a way that it hits the center of the target. Two learning algorithms are proposed and compared to learn the bi-manual skill: one with Expectation-Maximization based Reinforcement Learning,...
This paper proposes a plausible approach for a robot to discover its own body based on the coherence of two different sensory feedbacks; vision and proprioception. The image cues of a moving region are stored in an image base with a visuo proprioceptional coherence label. The existence of coherence between the vision and proprioception suggests that the visually detected object is correlated to its...
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...
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...
This paper proposes a simple tactile sensing and control method for robot to realize an active object surface recognition. The tactile sensor implemented on the robot hand consists of three force sensitive resistors with the peripheral circuits. The robot arm equipped with the sensor can perform active object recognition. Our research goal is to realize an effective robot controller for the 3D object...
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...
Novel fixed-length decimal encoding mechanism is proposed, which is for techniques of path planning of mobile robot based on an improved genetic algorithm. Effective path grids are adopted to identify the robot's motion surrounding. The obstacles can be described as polygons based on the given grids. The only vertexes of every obstacles polygon have corresponding unique decimal series value by the...
This paper describes a novel approach of autonomous navigation for a mobile robot based on a passive RFID that will be used in human living environment. Conventional approaches using dead reckoning or landmark are influenced by disturbances such as the light condition and obstacles, while the proposed method can obtain environmental information more reliably and robustly with the RFID system. The...
On cardiac resynchronization therapy, the right position for implantation of a pacemaker on the lateral wall of the left ventricle (LV), is the most important point for the surgical success. However, the past researches of the heart modeling have been developed the common heart model which has difficulty in application to individual diagnosis. Therefore the individual heart models which include individual...
Principal component analysis (PCA) has been applied in various areas such as pattern recognition and data compression. In some cases, however, PCA does not extract the characteristic of the data-distribution efficiently. In order to overcome this problem, we have proposed a novel method of nonlinear PCA which preserves the order of principal components. In this paper, we reduce the dimensionality...
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