5 papers
OVGrasp: Open-Vocabulary Grasping Assistance via Multimodal Intent Detection
Chen Hu, Shan Luo, Letizia Gionfrida
Grasping assistance is essential for restoring autonomy in individuals with motor impairments, particularly in unstructured environments where object categories and user intentions…
Imitation Learning for Adaptive Control of a Virtual Soft Exoglove
Shirui Lyu, Vittorio Caggiano, Matteo Leonetti +2
The use of wearable robots has been widely adopted in rehabilitation training for patients with hand motor impairments. However, the uniqueness of patients' muscle loss is often ov…
MultiClear: Multimodal Soft Exoskeleton Glove for Transparent Object Grasping Assistance
Chen Hu, Timothy Neate, Shan Luo +1
Grasping is a fundamental skill for interacting with the environment. However, this ability can be difficult for some (e.g. due to disability). Wearable robotic solutions can enhan…
Point Cloud-based Grasping for Soft Hand Exoskeleton
Chen Hu, Enrica Tricomi, Eojin Rho +4
Grasping is a fundamental skill for interacting with and manipulating objects in the environment. However, this ability can be challenging for individuals with hand impairments. So…
PointGrasp: Point Cloud-based Grasping for Tendon-driven Soft Robotic Glove Applications
Chen Hu, Shirui Lyu, Eojin Rho +3
Controlling hand exoskeletons to assist individuals with grasping tasks poses a challenge due to the difficulty in understanding user intentions. We propose that most daily graspin…