Making sense of words: a robotic model for language abstraction

Building robots capable of acting independently in unstructured environments is still a challenging task for roboticists. The capability to comprehend and produce language in a 'human-like' manner represents a powerful tool for the autonomous interaction of robots with human beings, for better understanding situations and exchanging information during the execution of tasks that require cooperation. In this work, we present a robotic model for grounding abstract action words (i.e. USE, MAKE) through the hierarchical organization of terms directly linked to perceptual and motor skills of a humanoid robot. Experimental results have shown that the robot, in response to linguistic commands, is capable of performing the appropriate behaviors on objects. Results obtained in case of inconsistency between the perceptual and linguistic inputs have shown that the robot executes the actions elicited by the seen object

Coevolution of active vision and feature selection

Abstract.: We show that complex visual tasks, such as position- and size-invariant shape recognition and navigation in the environment, can be tackled with simple architectures generated by a coevolutionary process of active vision and feature selection. Behavioral machines equipped with primitive vision systems and direct pathways between visual and motor neurons are evolved while they freely interact with their environments. We describe the application of this methodology in three sets of experiments, namely, shape discrimination, car driving, and robot navigation. We show that these systems develop sensitivity to a number of oriented, retinotopic, visual-feature-oriented edges, corners, height, and a behavioral repertoire to locate, bring, and keep these features in sensitive regions of the vision system, resembling strategies observed in simple insect

Emergence of Leadership in a Group of Autonomous Robots

For modern biology and ethology, the reason for the emergence of leaders-followers patterns in groups of living organisms, is the need of social coordination. In this paper we attempt to examine factors contributing to the emergence of leadership, trying to understand the relation between leader role and behavioral capabilities. In order to achieve this goal, we use a simulation technique where a group of foraging robots has to choose between two identical food zones. Thus, robots must coordinate in some way in order to select the same food zone and collectively gathering food. Behavioral and quantitative analysis indicate that a form of leadership emerges and the emergence of leadership relates with high level of fitness. Moreover, we show that more skilled individuals in a group tend to assume a leadership role, in agreement with literature

GAUSSIAN MIXTURE MODELS FOR THE ANALYSIS OF WISC-IV DIMENSIONS: A MULTIVARIATE APPROACH TO IMPROVE THE ASSESSMENT OF INTELLECTUAL FUNCTIONING

The Wechsler Intelligence Scale for Children-IV provides four indexes that analyze the intellectual functioning in specific cognitive fields and a full-scale intelligence quotient (FSIQ) as a measure of the general cognitive ability. However, often the diagnostic process considers the FSIQ score only. This study exploits the Gaussian mixture model (GMM) as a statistical tool to analyze WISC-IV capability to support the diagnostic decision-making process in a multidimensional approach based on the joint evaluation of the four main indexes. The study was conducted on two groups of participants (10 and 12 years old with N=52 and N=47, respectively) with clinical diagnosis. In addition, N=50 observations were randomly generated from the distribution of the Italian reference populations referred to each age group. In both groups, GMM detected two components underlining different behaviors in central tendency, variability, and correlation. Comparison of GMM partitions with a supervised classification shows that group memberships are congruent

Educational Robotics to Foster and Assess Social Relations in Students' Groups

Robotics has gained, in recent years, a significant role in educational processes that take place in formal, non-formal, and informal contexts, mainly in the subjects related to STEM (science, technology, engineering, and mathematics). Indeed, educational robotics (ER) can be fruitfully applied also to soft skills, as it allows promoting social links between students, if it is proposed as a group activity. Working in a group to solve a problem or to accomplish a task in the robotics field allows fostering new relations and overcoming the constraints of the established links associated to the school context. Together with this aspect, ER offers an environment where it is possible to assess group dynamics by means of sociometric tools. In this paper, we will describe an example of how ER can be used to foster and assess social relations in students' group. In particular, we report a study that compares: (1) a laboratory with robots, (2) a laboratory with Scratch for coding, and (3) a control group. This study involved Italian students attending middle school. As the focus of this experiment was to study relations in students' group, we used the sociometric tools proposed by Moreno. Results show that involving students in a robotics lab can effectively foster relations between students and, jointly with sociometric tools, can be employed to portrait group dynamics in a synthetic and manageable way

Construction of a Test Facility for Demonstration of a Liquid Lead-bismuth-cooled 10 kW Thermal Receiver in a Solar Furnace Arrangement - SOMMER

AbstractLiquid metals have been proposed in the past as high temperature heat transfer media in concentrating solar power (CSP) systems. Until the mid 80s test facilities were operated with liquid sodium-cooled central receivers. After a period of reduced interest in that approach, several new efforts have been reported recently, particularly from the US, South Africa and Australia. In addition, several recent publications have highlighted the attractive properties of liquid metals for CSP applications. A new contribution to this topic has been launched by Karlsruhe Institute of Technology (KIT) and the Solar Institute of the German Aerospace Center (DLR), combining their experience in CSP and liquid metal technology. The overall goals of this project are planning, design, construction and operation of a small concentrating solar power system in the 10kW thermal range (named SOMMER) using liquid metal as heat transfer fluid for re-gaining operation experience and validating design methodology and providing a complete design concept for a large pilot CSP plant based on liquid metal technology, up to evaluation of O&M cost and levelized cost of electricity. This paper describes the current status of the work on the design and setup of SOMMER, the research goals of this facility, first results of numerical activities in view of the liquid metal cooled receiver design and the connection to the design activities for the pilot plant

Coevolution of active vision and feature selection

We show that complex visual tasks, such as position- and size-invariant shape recognition and navigation in the environment, can be tackled with simple architectures generated by a coevolutionary process of active vision and feature selection. Behavioral machines equipped with primitive vision systems and direct pathways between visual and motor neurons are evolved while they freely interact with their environments. We describe the application of this methodology in three sets of experiments, namely, shape discrimination, car driving, and robot navigation. We show that these systems develop sensitivity to a number of oriented, retinotopic, visual-feature-oriented edges, corners, height, and a behavioral repertoire to locate, bring, and keep these features in sensitive regions of the vision system, resembling strategies observed in simple insects