Manip4Care: Robotic Manipulation of Human Limbs for Solving Assistive Tasks

TL;DR

Manip4Care introduces a modular simulation pipeline enabling robots to grasp and reposition human limbs for assistive tasks, addressing the limitations of static human assumptions in assistive robotics.

Contribution

This work presents a novel simulation framework with biomechanical and collision-aware grasping and repositioning methods for assistive robotic limb manipulation.

Findings

Effective limb grasping using antipodal sampling with force closure

Successful repositioning with MPPI and vector-field control under constraints

Demonstrated in real-world mannequin and bed bathing tasks

Abstract

Enabling robots to grasp and reposition human limbs can significantly enhance their ability to provide assistive care to individuals with severe mobility impairments, particularly in tasks such as robot-assisted bed bathing and dressing. However, existing assistive robotics solutions often assume that the human remains static or quasi-static, limiting their effectiveness. To address this issue, we present Manip4Care, a modular simulation pipeline that enables robotic manipulators to grasp and reposition human limbs effectively. Our approach features a physics simulator equipped with built-in techniques for grasping and repositioning while considering biomechanical and collision avoidance constraints. Our grasping method employs antipodal sampling with force closure to grasp limbs, and our repositioning system utilizes the Model Predictive Path Integral (MPPI) and vector-field-based control method to generate motion trajectories under collision avoidance and biomechanical constraints. We evaluate this approach across various limb manipulation tasks in both supine and sitting positions and compare outcomes for different age groups with differing shoulder joint limits. Additionally, we demonstrate our approach for limb manipulation using a real-world mannequin and further showcase its effectiveness in bed bathing tasks.