What, Where and How? Introducing pose manifolds for industrial object manipulation

Kouskouridas, Rigas; Amanatiadis, Angelos; Chatzichristofis, Savvas A.; Γαστεράτος, Αντώνιος

doi:10.1016/j.eswa.2015.06.039

Cited by 5 publications

(2 citation statements)

References 67 publications

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“…Over the years, rapid growth in robotics has been reported, improving a lot of developments in many fields, such as navigation and path planning [3,4], search and rescue applications [5], industrial applications [6], and entertainment. Considering the impact of the field, robots would inevitably be adapted for educational purposes also.…”

Section: Introductionmentioning

confidence: 99%

Computer Vision Meets Educational Robotics

et al. 2021

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Educational robotics has gained a lot of attention in the past few years in K-12 education. Prior studies have shown enough shreds of evidence and highlight the benefits of educational robotics as being effective in providing impactful learning experiences. At the same time, today, the scientific subject of computer vision seems to dominate the field of robotics, leading to new and innovative ideas, solutions, and products. Several articles from the recent literature demonstrate how computer vision has also improved the general educational process. However, still, the number of articles that connect computer vision with educational robotics remains limited. This article aims to present a systematic mapping review, with three research questions, investigating the current status of educational robotics, focusing on the synergies and interdependencies with the field of computer vision. The systematic review outlines the research questions, presents the literature synthesis, and discusses findings across themes. More precisely, this study attempts to answer key questions related to the role, effectiveness and applicability of computer vision in educational robotics. After a detailed analysis, this paper focuses on a set of key articles. It analyzes the research methodology, the effectiveness and applicability of computer vision, the robot platform used, the related cost, the education level, and the educational area explored. Finally, the results observed are referred to as educational process benefits. The reviewed articles suggest that computer vision contributes to educational robotics learning outcomes enhancing the learning procedure. To the best of our knowledge, this is the first systematic approach that revises the educational robotics domain by considering computer vision as a key element.

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Section: Introductionmentioning

confidence: 99%

Computer Vision Meets Educational Robotics

et al. 2021

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“…Early research just considered the global descriptors (shape, color, and texture) of an image as a single vector to perform the retrieval procedure [39,53]. Although using global features has advantages like low computational cost and categorizing natural landscapes images [76,175], it fails to browse images based on visual content. Therefore, extracting local features (LF) was considered in the next era of image retrieval methods [101].…”

Section: Image Retrievalmentioning

confidence: 99%