NDLI: DEMONSTRATION: Integrating Video Games and Robotic Play in Physical Environments

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DEMONSTRATION: Integrating Video Games and Robotic Play in Physical Environments

Content Provider	CiteSeerX
Abstract	Active Learning Environments with Robotic Tangibles (ALERT) are mixed reality video gaming systems that use sensors, vision systems, and robots to provide an engaging experience that may motivate hitherto underrepresented kinds of learners to become interested in game design, programming, and careers in science, technology, engineering, and mathematics. Through the use of fiducials (i.e., meaningful markers) recognized by robots through computer vision as just-in-time instructions, users engage in spatially-based programming without the encumbrances of traditional procedural programs ’ syntax and structure. Since humans, robots, and video environments share many inherently spatial qualities, this natural style of physical programming i s particularly well suited to fostering playful interactions with mobile robots in dynamic video environments. As these systems broaden the capabilities of video game technology and human-robot interaction (HRI) they are lowering many existing barriers to integrated video-robot game development and programming. Diverse ALERT video game scenarios and applications are enabling a broad range of gamers, learners, and developers to generate and engage in their own physically interactive games.
File Format	PDF
Access Restriction	Open
Subject Keyword	Integrating Video Game Physical Environment Robotic Play Broad Range Human-robot Interaction Spatially-based Programming Mobile Robot Just-in-time Instruction Active Learning Environment Playful Interaction Interactive Game Traditional Procedural Program Spatial Quality Mixed Reality Video Computer Vision Robotic Tangibles Physical Programming Vision System Video-robot Game Development Video Game Technology Meaningful Marker Natural Style Video Environment Share Diverse Alert Video Game Scenario Engaging Experience Dynamic Video Environment Hitherto Underrepresented Kind
Content Type	Text

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