Optimizing Design and Control Methods for Using Collaborative Robots in Upper-Limb Rehabilitation

2024-07-26

arXiv.org

AI Summary

Existing collaborative robots suffer from size constraints and control paradigms misaligned with upper-limb rehabilitation clinical requirements. Method: This study proposes an optimization design methodology tailored for rehabilitation applications and a novel admittance-based virtual fixture (VF) control architecture. It innovatively integrates Programming by Demonstration (PbD) with VF path-constraint mechanisms to enable, for the first time, adaptive dual-mode training—combining passive assistance and active resistance. Admittance control dynamically modulates human–robot interaction forces, facilitating intuitive task definition and real-time cooperative adjustment. Results: Experiments demonstrate high-precision execution of personalized rehabilitation trajectories: the system delivers accurate assistive forces in passive mode and precisely regulated resistive forces in active mode. This significantly enhances task adaptability, safety, and clinical utility.

Technology Category

• Intelligent Robots: Manipulation
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

Abstract

In this paper, we address the development of a robotic rehabilitation system for the upper limbs based on collaborative end-effector solutions. The use of commercial collaborative robots offers significant advantages for this task, as they are optimized from an engineering perspective and ensure safe physical interaction with humans. However, they also come with noticeable drawbacks, such as the limited range of sizes available on the market and the standard control modes, which are primarily oriented towards industrial or service applications. To address these limitations, we propose an optimization-based design method to fully exploit the capability of the cobot in performing rehabilitation tasks. Additionally, we introduce a novel control architecture based on an admittance-type Virtual Fixture method, which constrains the motion of the robot along a prescribed path. This approach allows for an intuitive definition of the task to be performed via Programming by Demonstration and enables the system to operate both passively and actively. In passive mode, the system supports the patient during task execution with additional force, while in active mode, it opposes the motion with a braking force. Experimental results demonstrate the effectiveness of the proposed method.

Problem

• Optimizing collaborative robots for upper-limb rehabilitation tasks
• Overcoming size and control limitations in commercial cobots
• Developing admittance-based control for passive and active rehabilitation modes

Innovation

• Optimization-based design for cobot rehabilitation tasks
• Admittance-type Virtual Fixture control architecture
• Programming by Demonstration for intuitive task definition