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This study extends existing Rubber Hand Illusion (RHI) experiments to employ life-size full-body humanlike android robot to investigate body ownership illusion and the sense of agency. For this study, we designed a novel experimental setting. The android robot moved synchronously with a participant's head and arm motion. Furthermore, a stereoscopic camera was mounted on the android's head and the...
This research proposes an integral system combining a hybrid BCI interface and shared control system for navigation and manipulation applications. In particular, the system consists of an electrical wheelchair with an embedded robotic arm that can assist a user to achieve essencial tasks such as picking up a cup of water. The proposed system uses a graphic interface that allows the user to select...
Healthcare demand for hospital beds is a concern in both private and public institutions. Conventional beds are cumbersome and do not consider caregiver's health, nor patient's stress and discomfort, which have consequences on the rehabilitation process. For these reasons, a mechatronic SmartBed system is proposed, designed with a user-friendly interface that empowers the patient and caregiver to...
The use of robots as educational tools has demonstrated to be highly effective for attracting students to science and technology related academic fields. Although these academic fields are very important, we believe that other subjects such as language, music, arts, literature, history, etc., are also essential for future generations. For this reason, the goal of this research is to explore the potential...
The objective of this research is to investigate the personality factors that influence human decision-making in particular scenarios such as during the interaction with a robot or a human counterpart. We conducted the experiment in a public environment in which participants were approached by either a human or a robot agent. The agent asked a verbal request in a direct or indirect manner that participants...
This paper presents a quantitative and qualitative analysis of the first robotics education workshop in which children and parents interact by experimenting with concepts of robotics. Unlike traditional robotics educational workshops that are targeted to children only, our initiative encourages children and parents to interact as a team and learn through ludic activities using a robotic kit. Therefore,...
In this paper we present IREP, an Interactive Robotics Education Program that aims to integrate basic concepts of mechatronics, electronics and computer science for undergraduate engineering students in an interactive manner. Our methodology is inspired in the process in which project management techniques are used in order to define goals, milestone planning is used to guide the implementation, scheduling...
This paper presents a preliminary analysis of the first robotics education workshop in which parent and children interact by experimenting with concepts of robotics and develop problem solving skills. Unlike traditional robotics education workshops targeted to children only, our initiative encourages both parent and children to interact as a team and become interested in science and technology. Post-workshop...
In this research we present a non-invasive Brain-Machine Interface (BMI) system that allows patients with motor paralysis conditions to control electronic appliances in a hospital room. The novelty of our system compared to other BMI applications is that our system gradually becomes autonomous by learning user actions (i.e. turning on/off window, lights, etc.) under certain environment conditions...
Pattern detection algorithms may be used as part of safety-relevant processes employed by industrial systems. Current approaches to functional safety mainly focus on random faults in hardware and the avoidance of systematic faults in both software and hardware. In this paper we build on the concepts of the international standard for functional safety IEC 61508 to extend safety-relevant notions to...
In this paper we present our semi-supervised technique for building object category classifiers using real image data from the Internet. Our technique not only reduces the overhead of manual training by humans, but also achieves robust classifiers that can be evaluated in real time. Given a sample object and its name (keyword), we collect a large amount of object-related images from two main image...
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