Do You Need a Hand? -- a Bimanual Robotic Dressing Assistance Scheme

Abstract

Developing physically assistive robots capable of dressing assistance has the potential to significantly improve the lives of the elderly and disabled population. However, most robotics dressing strategies considered a single robot only, which greatly limited the performance of the dressing assistance. In fact, healthcare professionals perform the task bimanually. Inspired by them, we propose a bimanual cooperative scheme for robotic dressing assistance. In the scheme, an interactive robot joins hands with the human thus supporting/guiding the human in the dressing process, while the dressing robot performs the dressing task. We identify a key feature that affects the dressing action and propose an optimal strategy for the interactive robot using the feature. A dressing coordinate based on the posture of the arm is defined to better encode the dressing policy. We validate the interactive dressing scheme with extensive experiments and also an ablation study. The experiment video is available on https://sites.google.com/view/bimanualassitdressing/home

References in corpus (6)

• DeepPose: Human Pose Estimation via Deep Neural Networks
• Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects
• Tracking Human Pose During Robot-Assisted Dressing using Single-Axis Capacitive Proximity Sensing
• Contact Skill Imitation Learning for Robot-Independent Assembly Programming
• Learning Task-Parameterized Skills from Few Demonstrations
• Set-based State Estimation with Probabilistic Consistency Guarantee under Epistemic Uncertainty

Cited by in corpus (2)

• Robot Deformable Object Manipulation via NMPC-generated Demonstrations in Deep Reinforcement Learning
• Evaluating the Pre-Dressing Step: Unfolding Medical Garments Via Imitation Learning