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Enhancing Independence through Intelligent Robotics: An AI Driven Assistive Robotics Interface

  • Applying methods in artificial intelligence to the field of assistive robotics has the potential to increase the independence of people with disabilities. The usage of AI to realize a shared control in this context is controversial, due to the high complexity of everyday tasks and the needed safety requirements. This paper presents the development of a user interface for AI-driven assistiveApplying methods in artificial intelligence to the field of assistive robotics has the potential to increase the independence of people with disabilities. The usage of AI to realize a shared control in this context is controversial, due to the high complexity of everyday tasks and the needed safety requirements. This paper presents the development of a user interface for AI-driven assistive robotic arms (ARA) that aims to assist people with physical disabilities in performing daily activities. This interface allows the user to select object manipulation tasks based on the objects recognized in a live video stream. Further, we compare several state-of-the-art, real-time object detection models to facilitate automatic robotic control. The results demonstrate the feasibility of the model and its potential integration into the overall robotic system.show moreshow less

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Metadaten
Document Type:Conference Proceeding
Conference Type:Konferenzartikel
Zitierlink: https://opus.hs-offenburg.de/10028
Bibliografische Angaben
Title (English):Enhancing Independence through Intelligent Robotics: An AI Driven Assistive Robotics Interface
Conference:The Upper Rhine Artificial Intelligence Symposium (5. : 16-17 November 2023 : Mulhouse, France)
Author:Katrin-Misel PonomarjovaStaff MemberORCiD, Thomas WendtStaff MemberORCiDGND, Anke Fischer-JanzenStaff MemberORCiD, Sinan SümeStaff MemberORCiD, Bastian Kayser
Year of Publication:2024
Creating Corporation:ENSISA-IRIMAS
Page Number:9
First Page:50
Last Page:58
Parent Title (English):UR-AI2023 : The Upper-Rhine Artificial Intelligence Symposium : Artificial Intelligence for Time Series, Robotics and Beyond
Editor:Jonathan Weber, Jean-Philippe Lauffenburger
URL:https://urai2023.sciencesconf.org/data/pages/book_urai2023_en_2024.pdf
URN:https://urn:nbn:de:bsz:ofb1-opus4-100285
Language:English
Inhaltliche Informationen
Institutes:Fakultät Wirtschaft (W)
Collections of the Offenburg University:Bibliografie
GND Keyword:Künstliche Intelligenz
Tag:Assistive Robotics; Human-Robot Interaction; Real-Time Object Detection
Formale Angaben
Relevance for "Jahresbericht über Forschungsleistungen":Konferenzbeitrag: h5-Index < 30
Open Access: Open Access 
 Bronze 
Licence (German):License LogoUrheberrechtlich geschützt