Learn More
We present a study of neural network architectures able to internally simulate perceptions and actions. All these architectures employ the novel Associative Self-Organizing Map (A-SOM) as a perceptual neural network. The A-SOM develops a representation of its input space, but in addition also learns to associate its activity with an arbitrary number of(More)
— The Ikaros project started in 2001 with the aim of developing an open infrastructure for system-level brain modeling. The system has developed into a general tool for cognitive modeling as well as robot control. Here we describe the main parts of the Ikaros system and how it has been used to implement various cognitive systems and to control a number of(More)
We have experimented with proprioception in a bio-inspired self-organizing haptic system. To this end a 12 d.o.f. anthropomorphic robot hand with proprioceptive sensors was developed. The system uses a self-organizing map for the mapping of the explored objects. In our experiments the system was trained and tested with 10 different objects of different(More)
Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors, as well as life habits, may affect semen quality. Artificial intelligence techniques are now an emerging methodology as decision support systems in medicine. In this paper we compare three artificial intelligence(More)
We review a number of self-organizing-robot systems that are able to extract features from haptic sensory information. They are all based on self-organizing maps (SOMs). First, we describe a number of systems based on the three-fingered-robot hand, i.e., the Lund University Cognitive Science (LUCS) Haptic-Hand II, that successfully extracts the shapes of(More)
Several recent works deal with 3D data in mobile robotic problems, e.g. mapping or egomotion. Data comes from any kind of sensor such as stereo vision systems, time of flight cameras or 3D lasers, providing a huge amount of unorganized 3D data. In this paper, we describe an efficient method to build complete 3D models from a Growing Neural Gas (GNG). The(More)