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Teaching computer science to children is a major priority in most countries in the world. Nevertheless, Computer Science curricula do not seem to address he children's world, children who need specific languages, models, and presentation methods. In this paper we propose a novel approach of considering a Computer Science Education curriculum based on children's creativity and imagination. The scope is the computer organization (aka Level 1 in he ACM K-12 Final Report). Materials have been designed for children, teachers and parents and take a gender-neutral approach.

Developing Computer Science curricula for children is a priority in most countries. In Italy, for example, the Minister of Education has recently reformed the Primary School curricula (6 to 10 years old). One of the main priorities concerns Computer Science.However, CS curricula for children do not seem to take into account "their particular world", since they are an "abstraction" or a reduction of classical Computer Science curricula for adults. In addition, children CS curricula are often left as the last topic of the "rethinking processes" in the Academic courses of Computer Science.Amazingly, there is a lack of attention on the "crucial" age for the development of many features concerning intellect and personality. New approaches need to be worked out to enhance children's imagination, so as to help them to better understand CS topics. The goal should not be devoted to CS Literacy, i.e. specific-but-limited applications. Indeed, the major objective must consider CS Fluency, i.e. building "solid bases" for CS knowledge.The process of rethinking Computer Science curricula, especially for children and youth does not seem to have started yet. There are many confirming signals on this. One of the most important evidence is a recently published and detailed analysis,"Oversold and Underused. Computers in the classroom" by Larry Cuban (2001). The computer is taught as a mere tool which reshapes, restructures, resembles and substitutes other domestic devices: the typewriter, the game machine, the CD/DVD player, the TV and the Radio, and so on. As a result, creativity, one of the essential ingredients of a child, is still missing.Following these inadequate practices, children cannot learn, explore or find their own solutions, nor can they follow their ideas or try out new tools. On the contrary, children need to focus on imagination, self-identification, analogy, play, and many other features characterizing their bubbling world.At the University of Verona, we have been developing an original and well founded CS course for future children's teachers. The whole CS course is composed of eight modules, each one referring to features of a "Realm" (i.e. the PC): archivists, secret agents, carriers to the external world, travelling companies, ambassadors and Masters. The approach is designed to gain the child's interest; indeed, the story itself, how the people of the realm interact with each other and how they behave will attract and entertain the child. In the meantime, in this way, the student will also gain a deep understanding of computer architecture. This is the rationale lying at the basis of our research.Although at present there is no statistical evidence to support this contention, first feedbacks are encouraging: firstly, teachers have sufficient material and content (figures, novel ways of describing the hardware, ideas on how to describe hardware functioning principles) in order to prepare children's lessons; secondly, the children show deep interest in the "hidden" parts of the computer; and finally, their parents are also "absorbed" by the material.However, a highly efficient research team is needed to reach scientific results, statistical evidence, further development, etc. Is anyone interested in creating "The fellowship of the CS children"?

In this paper we present a mapping paradigm for large scale precise navigation that takes inspiration from the bees' large scale navigation behavior. Navigation is performed through the use of two distinct sets of landmarks: global landmarks guide roughly the agent to a place, with local landmarks the agent performs very precise motion to the final destination. The paradigm is equivalent to a map composed of two distinct levels: with the first level, the agent navigates from place to place (topological navigation) following the global potential function. When the agent is close to the place of interest then it switches to a finer map of the specific place represented by a local potential function (second level). The general idea behind the article (2 levels hierarchical mapping and navigation) has been successfully used so far in the robotics literature. By the way, a robot that uses only one sensor, a color camera, and operates in real time with global and local self extracted natural unprocessed visual landmarks has not been presented yet. A prototype of the motion algorithm has been developed and diverse experiments and tests operating with a nomad 200 have been performed to prove the performance of the topological algorithm.

Teaching computer science to children is a big priority among the most of the EU Countries. Nevertheless, off-the-shelf Computer Science books are not particularly tailored to children, who rather need their own language, which is based on fantasy, self-identification, analogy, play, and diverse other features which characterize their bubbling world. These are the main motivations for the introduction of a novel and more children-oriented approach to Computer Science.The manual in use at the University of Verona illustrates the hardware components of a PC. It is composed of eight Chapters. Under the child's point of view, the PC is a Realm where diverse Subjects coexist together. The Realm is lead by His Majesty whose name is Si Piuh. The Mother and the servants are necessary for Si Piuh to complete the job. In this work we'll examine some features of the first chapter where the principal hardware components are presented.The hardware components can be imagined as people who live in a Realm. All the people of the Realm are Goblins, each one devoted to a particular role.With a bit of fantasy, in a Realm there are exactly the same relationships one can find in a PC: gates to the external world, artists who produce paintings and sounds, Masters who guide the whole process, libraries to store material, buses to transport material, ambassadors who know communication protocols, servants and as many other Subjects as one can imagine.The PC (i.e. the Realm) is lead by the CPU, i.e. His Majesty. The name of the king is Si Piuh, which stands for the Italian pronounce of CPU (fig. 1). Synchronizing all the activities inside the PC is a very hard work. By analogy, leading the Realm is not as easy as one can think.

This paper proposes a new geometrical structure for stereoscopic vision using omnidirectional cameras. The motivation of this work comes from the desire to equip a small hopping robot with an efficient and robust vision system to perform self localization during exploration missions. Because of size and weight constraints, we selected the Panoramic Annular Lens, for which no geometric model of stereo configuration was available. The paper describes the geometrical optical properties of the single lens and proposes a configuration for doing stereo vision with this lens. The analytical properties as well as the requirements of the complete system are discussed in the paper.

The use of landmarks is a natural and instinctive method to determine the whereabouts of a location or a means to proceed to a particular location. Results provided in this paper indicate that landmark-based navigation possesses a corrective or feedback trait that produces a convergence bound on the movements to the goal position, in contrast to the odometry-based movement, which leads to the drift between successive navigation movements. Experiments show that the vector field approach can be used to explain the convergence property of landmark-based guidance tasks. Experiments have been carried out operating with a Nomad mobile robot equipped with real-time visual landmark tracking system.

We propose a new method for real time obstacle avoidance using visual information. It is based on our on-going research on vector fields and potential functions associated to successful motion planning algorithms. Specifically, this paper addresses the avoidance of dynamic obstacles which have the property of producing instabilities in the navigation vector field associated to a planning algorithm. We show how avoidance maneuvers can be seen as a reaction to potential field instabilities measured by the moving robot. The paper briefly summarizes the analytical derivation of this approach, and discusses the results of planning experiments carried out using a Nomad200 robot with a landmark-based planning and navigation systems.

Different working principles are often considered when different visual behaviors are implemented in an agent. This occurs basically because the physical interaction between the behavior and the environment is not studied in depth. The paper shows how apparently different visual behaviors share common theoretical principles for their working mechanism. In particular properties related to the navigation vector field they compute in the environment, provide a base to explain visual learning, guidance, topological navigation, sub goal placement, obstacle avoidance and navigation enhancement. To handle the mathematics of a vector field robust tools are needed. Techniques borrowed from computer vision literature provide the necessary mathematical tools. All behaviors described have been tested in real robots. On going research is still in progress for topological navigation and subgoal placement.

This paper introduces a theory to formally and practically analyze the robustness issues of visual guidance methods for robot navigation. The first aspect is related to the convergence of the navigation system to the goal. It is shown how the dynamic system which drives the strategies can be analyzed by using classical concepts such as the Lyapunov functions. The second aspect concerns the conservativeness of the resulting navigation vector fields. It is shown how this deals with the repeatability of the trials. Furthermore, the selection of the best landmarks to perform the navigation processes strongly affects the conservativeness thus providing a formal way to do landmark learning. The theory has been tested with two different visual methods that have been derived from the biological world: the snapshot model and the landmark model.

This paper analyzes the effects of the application of visual adaptation mechanisms on snapshot-based guidance methods. The guidance principle of the visual homing is proven to be a visual potential function with an equilibrium point located at the goal position. The presence of a potential function means that classical control theory principles based on the Lyapunov functions can be applied to assess the robustness of the navigation strategy. The proposed adaptation mechanism is the Retinex algorithm, a blind chromatic adaptation pre-filtering that performs color constancy with no a priori information about the illuminant. It increases the visual information similarity under changes in the illuminant, increasing the robustness of the visual guidance. Tests and comparisons are presented.

Biology often offers valuable example of systems both for learning and for controlling motion. Work in robotics has often been inspired by these findings in diverse ways. Though the fundamental aspects that involve visual landmark learning and motion control mechanisms have almost exclusively been approached heuristically rather than examining the underlying principles. In this paper we introduce theoretical tools that might explain how the visual learning works and why the motion is attracted by the pre-learnt goal position. Basically, the theoretical tools emerge from the navigation vector field produced by the visual behaviors. Both the learning process and the navigation scheme influence the motion field. We apply classical mathematical and dynamic control to analyze the efficiency of our method.

Presents a biologically-inspired method for navigating using visual landmarks which have been self-selected within natural environments. A landmark is a region of the grabbed image which is chosen according to its reliability measured through a phase (turn back and look) that mimics the behavior of some social insects. From the self-chosen landmarks suitable navigation information can be extracted following a well known model introduced in biology to explain the bee's navigation behavior. The landmark selection phase affects the conservativeness of the navigation vector field thus allowing us to explain the navigation model in terms of a visual potential function which drives the navigation to the goal. The experiments have been performed using a Nomad200 mobile robot equipped with monocular color vision.