Robotic systems have a high potential for creative learning if they are flexible, accessible and engaging for the user in the experimental process of building and programming robots. In this paper we describe the Fable modular robotic system for creative learning which we develop to enable and motivate anyone to build and program their own robots. The Fable system consists of self-contained modules equipped with sensors and actuators, which users can use to easily assemble a wide range of robots in a matter of seconds. The robots are user-programmable on several levels of abstraction ranging from a simple visual programming language to powerful conventional ones. This paper provides an overview of the design of Fable for different user groups and an evaluation of critical issues when we attempt to integrate the system into an everyday teaching context.

This paper describes a tangible interface, Playte, designed for children animating interactive robots. The system supports physical manipulation of behaviors represented by LEGO bricks and allows the user to record and train their own new behaviors. Our objective is to explore several modes of interaction, i.e. direct remote control, tangible programming, programming by demonstration, and programming by training, to learn the design principles for more accessible, engaging, and playful robots. We evaluate the system experimentally and report on key observations from play sessions. We conclude that Playte facilitates playful activities and is appropriate for the intended target group (age 6+). Further, we discuss lessons learned regarding pros and cons of the different supported interactions modes.

In this paper, we describe the concept of remixing playware, which allows sampling and remixing of both physical and functional (e.g. music content) aspects of a system. Such remixing playware has a number of distinguished features which are explained in the paper: user-configurable modularity, which allows the user to interact and manipulate with samples; user-guided behavior-based system, which allows music compositions to emerge from the way performer interacts with the instruments that provide the primitive behaviours; intelligent sampling as the ability of creating samples that allow anybody to remix with the samples ensuring an engaging outcome. The paper exemplifies remixing playware with a variety of implementations in RoboMusic concerts, the virtual MusicTiles app, the physical MagicCubes, the physical dices in Peter Gabriel concerts, and the S'n'S system. These examples focus on music creation and performance, based upon the concept of RoboMusic, and it is argued that the concept of remixing playware extends to many other application areas of playware.

We are developing the Fable modular robotic system as a playware platform that will enable non-expert users to develop robots ranging from advanced robotic toys to robotic solutions to problems encountered in their daily lives. This paper presents the mechanical design of Fable: a chain-based system composed of reconfigurable heterogeneous modules with a reliable and scalable connector. Furthermore, this paper describes tests where the connector design is tested with children, and presents examples of a moving snake and a quadruped robot, as well as an interactive upper humanoid torso.

The development of physical interactive games demands extensive knowledge in engineering, computer science and gaming. In this paper we describe how the Modular Interactive Tiles System (MITS) can be a valuable tool for introducing students to interactive parallel and distributed processing programming for physical games development. This is done by providing an educational tool that allows a change of representation of the problems related to game designing from a virtual to a physical representation. Indeed, MITS seems to be a valuable system for bringing into education a vast number of issues (such as parallel programming, distribution, communication protocols, master dependency, connectivity, topology, island modeling software behavioral models, adaptive interactivity, feedback, user and multi-user game interaction, etc.). This can both improve the education-related issues in computer science classes, and enhance the younger and older gamers with a highly interactive and physical experience. We illustrate how the MITS system can be considered a tool for easy, fast, and flexible hands-on exploration of these issues, and through examples show how to implement interactive parallel and distributed processing in games with different software game models such as open loop, randomness based, rule based, user interaction based, AI and ALife based games, morphology based games, and physical teleplay games.

We describe how playware and games may adapt to the interaction of the individual user. We hypothesize that in physical games there are individual differences in user interaction capabilities and styles, and that adaptive playware may adapt to the individual user's capabilities, so that the activity automatically will match the capability of the individual user. With small test groups, we investigate how different age groups and gender groups physically interact with some playware games, and find indications of differences between the groups. Despite the small test set, the results are a proof of existence of differences and of the need for adaptation, and therefore we investigate adaptation as an important issue for playware. With simple playware games, we show that the adaptation will speed the physical game up and down to find the appropriate level that matches the reaction speed of the individual player. The appropriate level will change with game/interaction complexity, and adaptation finds the appropriate level for the individual player, even in multi-player games.

In this paper, we explore the design of modular robotic objects that may enhance playful experiences. The approach builds upon the development of modular robotics to create a kind of playware, which is flexible in both set-up and activity building for the end-user to allow easy creation of games. Key features of this design approach are modularity, flexibility, and construction, immediate feedback to stimulate engagement, activity design by end-users, and creative exploration of play activities. These features permit the use of such modular playware by a vast array of users, including disabled children who often could be prevented from using and taking benefits from modern technologies. The objective is to get any children moving, exchanging, experimenting and having fun, regardless of their cognitive or physical ability levels. The paper describes two prototype systems developed as modular robotic tiles, and discusses the challenges and opportunities of this modular playware when used by children with different cognitive abilities.

This paper outlines the use of modular robotics to encourage and facilitate nonverbal communication during therapeutic intervention in dementia care. A set of new socially interactive modular robotic devices called rolling pins (RPs) has been designed and developed to assist the therapist in interacting with dementia-affected patients. The RPs are semitransparent plastic tubes that are capable of measuring their orientation and the speed of their rotation; at a local level, they have three types of feedback: red, green, and blue light, sound, and vibration. The peculiarity of the RPs is that they are able to communicate with each other or with other devices equipped with the same radio communication technology. The RPs are usually used in pairs, as the local feedback of an RP can be set depending not only on its own speed and orientation but also on the speed and the orientation of the peer RP. The system is not used as a therapeutic toolpersebut as a facilitator and a mediator of social dynamics during normal therapy to counteract social isolation that can result in dementia through the loss of social skills. An experiment is reported that shows that by using the RPs, the patients participated in the activity by coordinating their behavior with the therapist and imitating the same interaction patterns generated by the therapist.

This paper presents an approach on how to adapt playgrounds using artificial neural networks (ANN). The playground consists of small tiles each capable of outputting coloured light, sensing force applied on them and communicating with neighbouring tiles. It is shown that a child's behaviour on the playground can be classified within eight categories by an ANN inputting the child's perception of the playground and the corresponding action performed; thus, enabling the playground to adapt real-time according to the classification. The playground has been developed, implemented and tested on a group of children. An ANN was trained using a subgroup of the children whose behaviour corresponds to the eight categories. Validating the ANN against the rest of the children's behaviours it was found that 96% were correctly classified. The trained ANN has been utilized in adapting the playground according to several playing strategies and validated by means of a statistical analysis of physiological signals (e.g. the heart rates of the children)

We used inspiration from modular robotics to create novel tools for dementia treatment based on activity analyses together with therapists and elderly in an Italian home care. This paper presents the technological development of such tools. In general, the tools are becoming part of a "multi-sensory room", i.e. a space augmented by innovative technologies, that can be configured for different therapeutic activities and needs and that leverages sensory stimulation. The development of the tools is inspired by modular robotics in order to allow for space re-configurability and adaptivity, which should support customized therapeutic interventions, and hopefully involve dementia affected users in the interaction with the solutions

Meaningful learning of information and communication technology (ICT) requires students to understand ICT concepts in their own cultural or societal context. In this study, we hypothesized that grounding ICT education in the local context and using concretizing tools, like programming visualization and intelligent building blocks (I-BLOCKs), would benefit students. We investigated this hypothesis by first developing an introductory ICT course in programming, which applied these strategies, and then by analyzing the results of the course. The course was held at Tumaini University, Iringa University College, Tanzania, in the fall of 2004. Altogether 27 teacher-trainees participated in the course. The outcomes of the course showed that the students understood the main concepts that were taught. They were also able to apply the methods of creative problem solving that were taught in the course. It was also found that students' algorithmically-oriented understanding was not at the desired level and that the course, as well as the future curriculum, needs further development in this particular area.

This paper describes the mechanical and electrical design of a new lattice based self-reconfigurable robot, called the ATRON. The ATRON system consists of several fully self-contained robot modules, each having their own processing power, power supply, sensors and actuators. The ATRON modules are roughly spheres with equatorial rotation. Each module can be connected to up to eight neighbors through four male and four female connectors. In this paper, we describe the realization of the design, both the mechanics and the electronics. Details on power sharing and power consumption is given. Finally, this paper includes a brief outline of our future work on the ATRON system.

Interaction between humans and traditional robotic systems can be problematic, as the traditional robotic systems often perform repetitive actions in a restricted environment, whereas human interaction is often characterized by novel ways of interactions, which creates an ever-changing environment. Therefore, traditional robotic system methods and technologies are often difficult to apply in situations and applications where the interaction plays a major role. So we developed a new kind of user-guided behavior-based robotics and applied this method to both mobile and humanoid robots, in order to investigate how nonexpert users could develop their own complex robot behaviors within a very short time (e.g., 30-60 min) with no prior knowledge of the robot technology. In the development of the team of humanoid robots, Viki, we used a modern approach to artificial intelligence that puts emphasis on the balance between control, electronic hardware, material, sensory system, and energy. It is possible to develop simple user interfaces with the user-guided behavior-based approach, in order to allow any user to design performances with the humanoid robots. However, we should not only look at the control of robots when designing human-robot interactions, but also on the physical aspects of the robotic system. Therefore, the novel concept of "programming by building" is introduced and exemplified with the creation of a prototype system consisting of building blocks with individual processing and communication capabilities. By assembling such building blocks, the user develops both the physical aspects and the functionality of the robotic system in an easy manner with no need to use a host computer or a traditional programming language. The approach is further exemplified with the implementation of neural building blocks that can later be trained by the user.

Behavioural experiments with crickets show that female crickets respond only to the male calling songs with a syllable rate within a specific interval, further it has been discovered that their response is independent of the duty-cycle of the song. Previously a neural control model was posed, which was able to explain how the selectivity of songs with syllable rates within a certain bandwidth could be obtained. The model explained why female crickets' response to calling songs was invariant to the duty-cycle of the songs. Here, we propose a new neural model, which is able also to account for the selectivity of a specific syllable rate and is invariant to the song duty-cycle. Implementing it on a small, mobile robot and using an analog electronic model of the peripheral auditory morphology of the female cricket as the sensor test the new model. The robot is placed under the same experimental conditions as the real crickets and it responds with phonotaxis to synthetic calling songs with syllable rates within a certain bandwidth similar to crickets. Further, the robot performs phonotaxis to songs with a syllable rate within the correct bandwidth independently of the duty-cycle of the song.

We developed spiking neural network control for a modular robotic system. The modular robotic system can be easily assembled by a user who is allowed to make overall behaviors by assembling the physical structure made up of a number of modules. The control of each module (building block) is implemented as a spiking neuron and action potentials are sent through the communication channels of the building blocks. We show how to make a mobile robot with these spiking neural building blocks. Hebbian learning is then applied to the spiking neuron building blocks in order to allow the mobile robot to adapt to changing environmental conditions. Collected data shows the learning process, sensor adaptation and performance on a simple task for the mobile robot made out of spiking neural building blocks.

During RoboCup'99 in Stockholm, we arranged the first RoboCup Jr. Here, the aim was to allow children hands-on experience with robotics, and for this purpose we set up a LEGO MINDSTORMS robot soccer game for children. We developed the user-guided behaviour-based approach in order to allow non-expert users to develop their own robots in an easy and fast manner. Indeed, using this approach, children of the age 7-14 were able to develop their own LEGO MINDSTORMS robot soccer players to play in nice and friendly tournaments with 60-90 minutes of development time! In a user-guided behavior-based system, it is the system developer who takes care of the difficult robotic problems, while the end-user is working on a higher abstraction level by making the coordination of primitive behaviors. Further, for the LEGO MINDSTORMS RoboCup Jr. game, we developed a field and a smart ball which allowed easy navigation and detection.

ortant fact is that the debate continues. The debate concerns the reliability of a robot as a model of the animal under study. In parallel, the arti cial life community enjoys its own, similar debate: can simulation of the real world be reliable, or is embodiment a necessity in order to gain understanding about life? The discussion about simulation vs. embodiment is by no means new, and actually many researchers in both \\camps" have been players in the other. For instance, some of arti cial intelligence's great theoreticians have previously tried to build robots. In the late 1950s, Minsky and others tried to build a ball catching robot (derived from the initial wish to build a ping-pong playing robot), and in the early 1970s, McCarthy tried to build an assembly robot (that should assemble a television kit) [4]. None of the projects succeeded, and as is well-known, both researchers have moved away from embodied arti cial intelligence. A typical argument for going towards simulation

Behavioral experiments with crickets show that female crickets respond to male calling songs with syllable rates within a certain bandwidth only. We have made a robot model in which we implement a simple neural controller that is less complex than the controllers traditionally hypothesized for cricket phonotaxis and syllable rate preference. The simple controller, which had been successfully used with a slowed and simplified signal, is here demonstrated to function, using songs with identical parameters to those found in real male cricket song, using an analog electronic model of the peripheral auditory morphology of the female cricket as the sensor. We put the robot under the same experimental conditions as the female crickets, and it responds with phonotaxis to calling songs of real male Gryllus bimaculatus. Further, the robot only responds to songs with syllable rates within a bandwidth similar to the bandwidth found for crickets. By making polar plots of the heading direction of the robot, we obtain behavioral data that can be used in statistical analyses. These analyses show that there are statistically significant differences between the behavioral responses to calling songs with syllable rates within the bandwidth and calling songs with syllable rates outside the bandwidth. This gives the verification that the simple neural control mechanism (together with morphological auditory matched filtering) can account for the syllable rate preference found in female crickets. With our robot system, we can now systematically explore the mechanisms controlling recognition and choice behavior in the female cricket by experimental replication.

Populations of simple artificial organisms modeled as neural networks evolve a preference for one particular food type in an environment that contains more than one food type if the quantity of energy extracted from each food type is allowed to coevolve with the behavioral preference (evolvable fitness formula). If, after the emergence of the food preference, the preferred food gradually disappears from the environment at the evolutionary time scale, the evolved specialist strategy is maintained until the preferred food type has completely disappeared. Then a new specialist strategy suddenly emerges with a preference for another food type present in the environment. The appearance of the new strategy takes very few generations, in fact much fewer than in a population starting from zero (random initial population) in the same environment. This, together with the fact that the population with an evolutionary past is more efficient than the population starting from zero, suggests that the former population is preadapted to the changed environment. An analysis of the activation values of the hidden units indicates that the new food preference can be an “exaptation,” that is, a new adaptation based on a structure that has previously emerged for adaptively neutral reasons.

The problem of the validity of simulation is particularly relevant for methodologies that use machine learning techniques to develop control systems for autonomous robots, as, for instance, the artificial life approach known as evolutionary robotics. In fact, although it has been demonstrated that training or evolving robots in real environments is possible, the number of trials needed to test the system discourages the use of physical robots during the training period. By evolving neural controllers for a Khepera robot in computer simulations and then transferring the agents obtained to the real environment we show that (a) an accurate model of a particular robot-environment dynamics can be built by sampling the real world through the sensors and the actuators of the robot; (b) the performance gap between the obtained behaviors in simulated and real environments may be significantly reduced by introducing a “conservative” form of noise; (c) if a decrease in performance is observed when the system is transferred to a real environment, successful and robust results can be obtained by continuing the evolutionary process in the real environment for a few generations.