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WLRI-AD: assistive device dataset for daily living automation

  • Depending on the degree of disability, simple tasks of daily living can be challenging for people with physical disabilities, such as picking up and placing objects, eating, or reaching for a cup to drink independently. Pervasive technologies such as robotic arms can be used to assist with these daily tasks, allowing patients to regain independence while reducing the need for care. SpecializedDepending on the degree of disability, simple tasks of daily living can be challenging for people with physical disabilities, such as picking up and placing objects, eating, or reaching for a cup to drink independently. Pervasive technologies such as robotic arms can be used to assist with these daily tasks, allowing patients to regain independence while reducing the need for care. Specialized devices, such as assistive forks or spoons, can facilitate these tasks. Image datasets of everyday objects such as MS COCO do not contain assistive devices, which tend to look different from their non-assistive counterparts. We present the dataset WLRI-AD (Work-Life Robotics Institute–Assistive Devices) to enable a robot to interact with devices in assisted living homes. The benefits of including assistive devices are demonstrated by comparing versions of the dataset with each other and to a baseline. Initial results show an improvement in the detection of assistive devices by training a YOLOv8 model on the assistive devices.show moreshow less

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Metadaten
Document Type:Article
Zitierlink: https://opus.hs-offenburg.de/12159
Bibliografische Angaben
Title (English):WLRI-AD: assistive device dataset for daily living automation
Author:Katrin-Misel PonomarjovaStaff MemberORCiD, Anke Fischer-JanzenStaff MemberORCiD, Thomas WendtStaff MemberORCiDGND, Kristof Van LaerhovenORCiD
Year of Publication:2026
Date of first Publication:2026/02/07
Place of publication:London
Publisher:Springer London
First Page:1
Last Page:10
Article Number:2
Parent Title (English):Personal and Ubiquitous Computing
Volume:30
Issue:1
ISSN:1617-4909 (Print)
ISSN:1617-4917 (Elektronisch)
DOI:https://doi.org/10.1007/s00779-026-01854-2
Language:English
Inhaltliche Informationen
Institutes:Fakultät Wirtschaft (W)
Research:WLRI - Work-Life Robotics Institute
Collections of the Offenburg University:Bibliografie
Tag:Assistive technology; Dataset; Object detection; YOLO
Formale Angaben
Relevance for "Jahresbericht über Forschungsleistungen":5-fach | Wiss. Zeitschriftenartikel reviewed: AGQ-Positivlisten
Open Access: Open Access 
 Hybrid 
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International