Robots and Cultural Heritage: New Museum Experiences

The introduction of new technologies to enhance the visiting museum experience is not a novelty. A large variety of interactive systems are nowadays available, including virtual tours, which makes cultural heritage accessible remotely. The theme of increase in accessibility and attractiveness has lately been faced with the employment of the service robotics, covering various types of applications. Regrettably, many of robotics solutions appear less successful in terms of utility and usability. On the basis of this awareness, a design for a new robotic solution for cultural heritage has been proposed. The project, developed at the royal residence of Racconigi Castle, consists of a telepresence robot designed as a tool to explore inaccessible areas of the heritage. The employed robot, called Virgil, was expressly designed for the project. The control of the robot is entrusted to the museum guides in order to enhance their work and enrich the cultural storytelling

Virgil Robot at Racconigi’s Castle: a Design Challenge.

This paper discusses the role of Design Research (DR) as a mediator between robotics and cultural heritage. This issue has been addressed in the project Virgil, a telepresence robot for visiting inaccessible areas of Racconigi Castle in Piedmont, Italy. A project developed applying an iterative design process that combines the traditional activities of design practice, such as product and service design, to a more theoretical and conceptual activities of DR aimed to generate a meaningful solution. Both the museum context and the state of the art of museum robotic applications have been analysed to define the ethical requirements for the development of the service. The analytical phase is followed by the design stage in which a service concept has been defined, through a process of continuous debate and co-design with various stakeholders. The process has led to the prototyping of a dedicated robot tested in the real environment with random visitors

Adaptiivinen tunnepohjainen päätösmalli sosiaaliselle robotille

This thesis introduces a computational model of emotions and decisions for a robot, which interacts meaningfully in a social context. The decision making framework is based on multi-attribute utility theory, but it contains a dynamic and adaptive emotional model which basically acts as a preference and perception manipulator. The emotional model is based on event appraisal with discrete emotion categories. Events are assessed using dimensions of utility and probability as well as expectations. The model uses the concepts of core affect and attributed affect to create a multilevel emotion consisting of moods and emotional events. Personality traits are used to create different emotional dynamics by modifying relevant parameters. Attitudes and relationships, understood through attributed affect and classical conditioning, make the robot emotions more believable. The robot learns from user actions and makes predictions about them and environment changes according to probabilistic models. Subjective well-being and human need hierarchy are used as the basis for the preferences which the visceral state affects. The model is inspired by the computational models Cathexis, FLAME, EMA, TAME and Roboceptionist, and is an expanded version of the model used in AISoy1 robot. The framework combines extensive psychological research and requires validationTyössä kehitetään tunteiden ja päätösten laskennallinen malli robotille, jotta se voisi käyttäytyä sosiaalisissa tilanteissa järkevästi. Päätöksentekomalli perustuu monitavoitteeseen arvoteoriaan, mutta sitä on muutettu niin, että tunnemalli säätelee mieltymyksiä sekä tulkintaa dynaamisesti ja mukautuvasti. Tunnemalli perustuu tapahtuma-arviointiin ja diskreetteihin tunnekategorioihin. Tapahtumia arvioidaan käyttämällä hyötyä, todennäköisyyksiä sekä odotuksia ulottuvuuksina. Malli käyttää ydintunnetilaa ja liitettyä tunnetilaa luodakseen monikerroksisen tunteen, joka sisältää mielialan ja tunteikkaita tapahtumia. Persoonallisuuspiirteillä saadaan aikaan monipuolisia tunnedynamiikkoja säätämällä asianmukaisia parametreja. Asenteet ja suhteet tekevät robotista uskottavamman, ja ne ymmärretään liitetyn tunnetilan sekä klassisen ehdollistamisen avulla. Robotti oppii käyttäjän teoista ja tekee niistä sekä ympäristön kehityksestä ennusteita todennäköisyyspohjaisilla malleilla. Subjektiivinen hyvinvointi ja ihmisen tarvehierarkia antavat mieltymysten painotukselle pohjan, jota robotin sisäinen tila muokkaa. Laskennalliset mallit Cathexis, FLAME, EMA, TAME and Roboceptionist inspiroivat mallia, joka on laajennettu versio AISoy1 robotin mallista. Kehys yhdistää laajaa psykologista tutkimusta ja vaatii testausta