Exploring Human-robot Interaction by Simulating Robots

As collaborative robots enter industrial shop floors, logistics, and manufacturing, rapid and flexible evaluation of human-machine interaction has become more important. The availability of consumer headsets for virtual and augmented realities has lowered the barrier of entry for virtual environments. In this paper, we explore the different aspects of using such environments for simulating robots in user studies and present the first findings from our own research work. Finally, we recommend directions for applying and using simulation in human-robot interaction

my2cents: enabling research on consumer-product interaction

Barcode scanners for smartphones enable mobile product-centric services for consumers. We have developed a mobile app that enables consumers to share their use of and opinions about products with their friends and others. Our goal is to establish a product-centric information stream generated by users to benefit other consumers and retail businesses and to enable large-scale research on consumer-product interaction. This paper describes our approach to create a sustainable service. We report first experiences and an initial evaluation after releasing the app to the public, give an overview over possible business models, and discuss some of the challenges we experienced during implementatio

Electric Mobility Roaming for Extending Range Limitations

Electric vehicles (EVs) are currently promoted by government and industry as an alternative to traditional internal combustion engine (ICE) propelled vehicles. However, e-mobility has not yet reached a level of technological maturity that allows for the same degree of mobility offered by ICE propelled vehicles. In this paper, we argue that the adaption of roaming concepts to enable EV charging across geographical and service provider boundaries is likely to be a crucial element for e-mobility to be successful. To that end, we derive requirements and design principles for roaming concepts in e-mobility. Furthermore, we present and briefly evaluate a prototype implementation of an e-mobility roaming platform as a proof-of-concept

Crowdsourcing for “Kiosk of the Future” – A Retail Store Case Study

This article reports on a case study which describes how Valora Retail, the company that operates the majority of Kiosks inSwitzerland, successfully completed a intermediary mediated Crowdsourcing project as well as the results they achievedusing this open innovation approach to generate ideas for the internal project named the “Kiosk of the Future”. Out of the626 ideas virtually submitted by the crowdsourcing community, 64 ideas were evaluated to be relevant for the project and the19 best ideas were given rewards and were considered for further internal analysis and development. This case study detailsthe process by which the top ideas were chosen and clearly demonstrates a successful application of Crowdsourcing for ideageneration for the early innovation process. It was reported that the achieved outcome of this project would unlikely haveoriginated from the company itself due to high internal barriers

Estimating Data Volumes of RFID-enabled Supply Chains

The widespread application of RFID tags in supply chains is said to cause enormous data volume problems and thus unprecedented challenges for systems and infrastructures. In order to unleash the potential of item-level RFID applications, such as data sharing and discovery across company boundaries, an unbiased understanding of emerging data volumes is necessary. However, quantitative data that provides factual argument is still scarce. Therefore, we present a simulation study based on a real-world scenario that reveals quantitative characteristics of the data volumes problem in an RFID-enabled supply chain and discuss its implications. Our results suggest that data volumes will be much lower than currently anticipated, but still bear significant challenges for researchers and developers of RFID infrastructures

Detecting incorrect product names in online sources for product master data

The global trade item number (GTIN) is traditionally used to identify trade items and look up corresponding information within industrial supply chains. Recently, consumers have also started using GTINs to access additional product information with mobile barcode scanning applications. Providers of these applications use different sources to provide product names for scanned GTINs. In this paper we analyze data from eight publicly available sources for a set of GTINs scanned by users of a mobile barcode scanning application. Our aim is to measure the correctness of product names in online sources and to quantify the problem of product data quality. We use a combination of string matching and supervised learning to estimate the number of incorrect product names. Our results show that approximately 2% of all product names are incorrect. The applied method is useful for brand owners to monitor the data quality for their products and enables efficient data integration for application providers