Abstract 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. 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.
Ponomarjova et al. (2026) studied this question.