Capability-based Frameworks for Industrial Robot Skills: a Survey

March 01, 2022 ยท The Cartographer ยท ๐Ÿ› 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Capability-based Frameworks for Industrial Robot Skills: a Survey"

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Authors Matteo Pantano, Thomas Eiband, Dongheui Lee arXiv ID 2203.00538 Category cs.RO: Robotics Citations 11 Venue 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) Last Checked 23 hours ago
Abstract
The research community is puzzled with words like skill, action, atomic unit and others when describing robots' capabilities. However, for giving the possibility to integrate capabilities in industrial scenarios, a standardization of these descriptions is necessary. This work uses a structured review approach to identify commonalities and differences in the research community of robots' skill frameworks. Through this method, 210 papers were analyzed and three main results were obtained. First, the vast majority of authors agree on a taxonomy based on task, skill and primitive. Second, the most investigated robots' capabilities are pick and place. Third, industrial oriented applications focus more on simple robots' capabilities with fixed parameters while ensuring safety aspects. Therefore, this work emphasizes that a taxonomy based on task, skill and primitives should be used by future works to align with existing literature. Moreover, further research is needed in the industrial domain for parametric robots' capabilities while ensuring safety.
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