Beyond Participatory Design for Service Robotics

The spread of technologies as Cloud and Distributed Computing, the Internet of Things (IoT) and Machine Learning techniques comes with highly disruptive innovation potential and consequent design imperatives. High connectivity of devices and machines is shaping not only sensing and monitoring capabilities, but also describing ever more ubiquitous and diffuse computing capabilities, affecting decision-making with a wide range of assisting tools and methods. With the scaling potential of moving beyond its contemporary application such as industrial facilities monitoring, precision farming and agriculture, healthcare and risk management scenarios, RaaS is bound to involve an increasingly fluid and diverse range of users, shaping new socio-technical systems where practices, habits and relationships will evolve in respect to its adoption. On these premises, applied research at Polytechnic Interdepartmental Centre for Service Robotics in Turin, Italy, focuses on the development of a service robotics platform able to operate on the local scale and capable of adapting to evolving scenarios

Participatory design for service robotics

The spread of technologies as Cloud and Distributed Computing, the Internet of Things (IoT) and Machine Learning techniques comes with a few paradigm changes with highly disruptive innovation potential and consequent design imperatives. Digital Abundance is a shorthand that introduces us to the economy of information as a non-depletable resource, as it can be continuously copied, while exponentially increased due to “cheap and small” sensor technology. High connectivity of devices and machines is shaping not only sensing and monitoring capabilities of different application fields, but also describing ever more ubiquitous and diffuse computing capabilities, affecting decision-making with a wide range of assisting tools and methods, like context-aware AI fuelled by a yet unmatched data flow. On these premises, applied research at Polytechnic Interdepartmental Centre for Service Robotics in Turin, Italy, focuses on the development of a service robotics platform able to operate on the local scale and capable of adapting to evolving scenarios. Useful to this purpose is Robotics-as-a-Service (RaaS) framework, a cloud computing service model that allows to seamlessly integrate robots and embedded (IoT) devices into Web and cloud computing environment. As a service-oriented architecture (SOA) for robotic applications, a RaaS unit has the environmental potential of decoupling the production of economic value from energy and resources consumption. It includes services for performing functionalities, a service directory for discovery and publishing, and service clients for user’s direct access. This platform allows to manage robotics components both as an increasingly granular integration of control over automated tasks and as part of a largely aware whole emerging from their connectivity. With the scaling potential of moving beyond its contemporary application such as industrial facilities monitoring, precision farming and agriculture, healthcare and risk management scenarios, RaaS is bound to involve an increasingly fluid and diverse range of users, shaping new socio-technical systems where practices, habits and relationships will evolve in respect to its adoption. For this product-service system we propose a Socio-Technical Innovation framework to balance the efficiency of simple stable technological systems with the capacity for resilience and adaptability of more complex, unstable social systems that surround them. Complex systems high connectivity leads to difficulties in centralized control and predicting causes and effects, driving the need of localizing decision-making when possible. Chances of identifying a single ‘optimal’ solution for the whole system width are low; great part of current information and implementation happen on a local scale, necessitating a decentralized approach. While in simple and stable systems homogeneity of input is favoured over a more problematic diversity, in complex social systems heterogeneity is incredibly more valuable, both increasing the range of current information and of solutions generated. A wider network of stakeholders, reaching out to growing community of users and producers, allows organizations to see more opportunities than those dependent on previous choices. Local decision-making made by a variety of actors with shared interests, is likely to be the most successful: though the larger system is complex and difficult to predict, its subunits are less so. Laying our foundations on Participatory Design (PD) research we propose the Actor-network social theory as a tool to analyse the intricate relationships that define the structure of groups where humans are not the are not the only participants, as artefacts concepts and design itself function as intermediary. Thinking of stakeholders in PD as a network of actors is useful as it allows researchers or designers to understand cultural practices, power relationships and the roles of mediating artefacts or concepts, as recognizing the mechanisms through which power is exercised is vital. In a User Experience Design context, a particularly useful term to describe possibilities of action emerging from the reciprocal relation between an actor and his environment, is affordance in its original definition proposed by psychologist J. J. Gibson in 1977. (Vardouli 2015). In his paper Vardouli argues that the notion of affordance could be analogized with the one of embedding, as they refer to possibilities for engagement of the subject with a context. To support heterogeneity of solutions fitting diverse use cases and even different application fields we investigate service robotics case studies for modular design, to generate a product-service system of non-independent solutions. A designed system of product components and services follows the purpose finding principle (Jones 2016). As Jones further explains in his paper on Systemic Design Principles, the purpose principle provides a whole-to-part view of problem space. The diversity of solutions provided by a modular configuration of functionalities, delivered in the form of services, guarantees a balance between fixed purposes and what Jones refers to as creative framing. We will then explore the literature on PD solutions to usability issues. To answer interrogatives about the collection of end user requirements, about their involvement in a continuous development process and how to achieve a common understanding among the actors, we look for methods to explicitly model the interaction relationships between server and client, producer and consumer, designer and user in order to increase the learning capacity of a RaaS ecosystem through the integration of diverse experiences, while distributing means of production and innovation capacity

Human-Machine Co-Living

The dichotomous, almost dystopian scenario that we face when we look at the current framework of technological develop- ment poses increasingly pressing questions for what regards the relationship that we, as a human kind, have with the digitised automation of our lives. Internet, robotics, data cloud computing and artificial intelligence are tools widely used in our society, however, we are not yet able to really get into this innovation and while we are looking for solutions, we do not live without a certain sense of inadequacy: we exploit innovation but got to come partly dependent on it, up to the point of producing social effects, sometimes even harmful. The intelligent human-machine relationship becomes a topic for further investigation when applied to the field of design and artefacts production, whereas in traditionally passive tech- nological environments humans work actively, determining conscious choices: the introductions of artificial intelligence determines a habits shift because it transforms the values in the field, it upsets them. Starting from principles and methods in some of the scenarios in which design traditionally acts, i.e. production, multidiscipli- nary connective relations, designed innovation, the application of collaborative strategies between human and artificial intelli- gence is hypothesized. It is therefore suggested an experiment useful to bring out the potential of the relationship between human beings and machines in place of the predisposition of rules of conduct that fix the roles by freezing them in the recipients and determining in fact the failure. The output scenario offers food for thought on values, power relations, connections and on how much local action is comple- mentary to a global complexity that can no longer be evaded; there, design in its bidirectional relations between subjects and components, provides on field experimental solutions, working closely to the subjects directly involved

Data Standards for Computational Ecology: constraining soft sub-systems to increase internal complexity for community resilience

The Creative Systemic Research Platform at the Design and Innovation College of Tongji University in Shanghai focuses on facilitating learning of a diverse set of organizations, researching on the quality of interactions occurring among different agents, both human and non, and their context. A major communication channel available today employs sensors to observe otherwise invisible conditions of the environment, enabling a detailed understanding of how patterns of interactions among biological elements influence the global conditions. To address some of the most urgent need resulting from urbanization, industrialization and globalization processes, in 2018 we started working on computational ecology to support agricultural practices delivering self-organization capacity in diverse human settlements. The complex web of interactions occurring in such a context calls for a rich qualitative analysis of its conditions. To start building knowledge models that fit diverse range of human agents, a case-study methodology is employed. Boundaries have been set to describe the diversity of the analysed contexts, ranging from urban indoor greenhouses to agro-forestry management, working on the edges of these systems to address functional clustering and distribution. The first case study reflects a semi-controlled environment to constrain the space and time of natural cycles of vegetation and water and the number of observable interactions as preconditions for a university class of Design Students to interact with an indoor greenhouse. This process led to work on the development of data standards for collection and integration protocols to embed qualitative observation. Ontological constraints in computational agriculture as a sub-system of living communities is key element to enable access to self-monitoring practice into farm management, distributing learning and adaptation capacity as basis for autonomous, ecologically fitting human settlements ready to address internal transformations

Augmented Video-Environment for Cultural Tourism

In this paper a series of reflections on the topicality of smart glasses for the tourist-cultural field are illustrated. Although this technology has received a setback in the consumer market in the past, nowadays it is back in the limelight thanks to the involvement of world leaders in fashion and social networks. The objective of this paper is to show that such wearable devices can be a resource for the dissemination and enhancement of the Cultural Heritage. This assumption forms the basis of the project proposal for an ‘augmented’ video-environment for cultural tourism, which is presented below. It is a theoretical-experimental project and proposes an approach to the augmented reality by using geolocation technologies and 3D mapping of the territory, overcoming the simple tourist approach to Cultural Heritage, perceiving, and displaying multimedia contents that enrich the real experience of the user in the artistic sense