58 research outputs found
EasySRRobot: An Easy-to-Build Self-Reconfigurable Robot with Optimized Design
No full textSelf-reconfigurable modular robots (SRRobot) that can change their shape and function in different environments according to different tasks have caught a lot of attention recently. Most existing prototypes use professional electronic components with relatively expensive cost and high barrier of fabrication. In this paper, we present a low-cost SRRobot with double-cube modules. Our system is easy-to-build even for novices as all electric components are off-the-shelf and the structural components in plastics are made by 3D printing. To have a better design of interior structures, we first construct a design space for all feasible solutions that satisfy the constraints of fabrication. Then, an optimized solution is found by an objective function incorporating the factors of space utilization, structural sound-ness and assembly complexity. Thirty EasySRRobot modules are manufactured and assembled. The functionality of our algorithm is demonstrated by comparing an optimized interior design with other two feasible designs and realizing different motions on an EasySRRobot with four modules.Accepted author manuscriptMaterials and Manufacturin
A PMJ-inspired cognitive framework for natural scene categorization in line drawings
No full textHumans' remarkable capacity on rapid natural scene categorization has been widely studied in neuroscience. Recently, a functional MRI (fMRI) study showed that in human brain, decoding of natural scenes from line drawings was very similar to those from color photographs. In this paper, based on recently proposed computational cognition model of Perception, Memory and Judgement (PMJ model), we investigate the computational model of line drawings and propose a PMJ-inspired cognitive framework for natural scene categorization in line drawings. The Ohio State University (OSU) dataset was used, which included 475 color photographs in six categories, i.e., beaches, city streets, forests, highways, mountains and offices, as well as 475 corresponding line drawings produced by trained artists. Experimental results show that our proposed cognitive framework achieves 48.4% recognition rate in leave-one-out cross-validation, which is much higher than fMRI-data-driven decoding accuracy in the visualprocessing hierarchy (29% in V1, 27% in V2+VP, 26% in V4, 29% in PPA and 23% in RSC). (C) 2015 Elsevier B.V. All rights reserved
Cognitive mechanism related to line drawings and its applications in intelligent process of visual media: a survey
No full text
Line drawings, as a concise form, can be recognized by infants and even chimpanzees. Recently, how the visual system processes line-drawings attracts more and more attention from psychology, cognitive science and computer science. The neuroscientific studies revealed that line drawings generate similar neural actions as color photographs, which give insights on how to efficiently process big media data. In this paper, we present a comprehensive survey on line drawing studies, including cognitive mechanism of visual perception, computational models in computer vision and intelligent process in diverse media applications. Major debates, challenges and solutions that have been addressed over the years are discussed. Finally some of the ensuing challenges in line drawing studies are outlined.</p
CoronaCast 2024: 3-Day Forecast
No full text<p>These are the model output data for the 3-day forecast of the total solar eclipse in April 8, 2024, using the Space Weather Modeling Framework (SWMF) at the University of Michigan. See README.txt for information on dataset contents, formats, and suggested software libraries.</p>
CoronaCast 2024: 3-Day Forecast
No full text<p>These are the model output data for the 3-day forecast of the total solar eclipse in April 8, 2024, using the Space Weather Modeling Framework (SWMF) at the University of Michigan. See README.txt for information on dataset contents, formats, and suggested software libraries.</p>
CoronaCast 2024: 1-Day Forecast
No full text<div>
<p>These are the model output data for the 1-day forecast of the total solar eclipse in April 8, 2024, using the Space Weather Modeling Framework (SWMF) at the University of Michigan. See README.txt for information on dataset contents, formats, and suggested software libraries.</p>
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CoronaCast 2024: 3-Day Forecast
No full text<p>These are the model output data for the 3-day forecast of the total solar eclipse in April 8, 2024, using the Space Weather Modeling Framework (SWMF) at the University of Michigan. See README.txt for information on dataset contents, formats, and suggested software libraries.</p>
CoronaCast 2024: 1-Day Forecast
No full text<div>
<p>These are the model output data for the 1-day forecast of the total solar eclipse in April 8, 2024, using the Space Weather Modeling Framework (SWMF) at the University of Michigan. See README.txt for information on dataset contents, formats, and suggested software libraries.</p>
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Tangible interaction with 3D printed modular robots through multi-channel sensors
No full textTangible interaction with customized products integrating sensors and actuators recently grows into an interdisciplinary research area in computer graphics and human-robot interaction (e.g., [Groeger et al. 2016; Yu et al. 2018]). In this paper, we introduce tangible interaction into 3D printed modular robots. Our user study demonstrates that interacting with our robots can effectively improve human spatial ability, which plays an important role during a person's development in science, technology, engineering or math (STEM)
Spatial Ability Improvement by Tangible Interaction
No full textSpatial ability is a category of human reasoning skills that plays an important role in affecting a person’s development in science, technology, engineering and mathematics. Spatial ability has been demonstrated to be malleable and can be improved through training. In this paper, we present a training scheme by tangible interaction with a reconfigurable robot called EasySRRobot. A preliminary user study based on behavioral and EEG data analysis shows that via interaction with EasySRRobot, users can significantly improve their performance on a task related to spatial ability. Copyright held by the owner/author(s)
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