Design, Dynamic Modeling and Control of a 2-DOF Robotic Wrist Actuated by Twisted and Coiled Actuators

2025-03-07

AI Summary

Dynamics modeling and high-precision control of artificial muscle–actuated robotic wrists have long been neglected. Method: This paper proposes a lightweight 2-DOF 3RRRR parallel wrist mechanism driven by twisted-and-coiled artificial muscles (TCAs). We establish its complete Lagrangian dynamic model for the first time and design a nonlinear model predictive controller (NMPC) for real-time trajectory tracking. Contribution/Results: Experimental evaluation on an embedded platform shows that NMPC reduces trajectory tracking error by 62% compared to conventional PID control, significantly improving robustness and dynamic response. The 3RRRR architecture inherently suppresses friction while enhancing structural stiffness and compactness. To our knowledge, this work provides the first systematic framework integrating modeling, control, and experimental validation for TCA-driven soft-rigid hybrid wrists—advancing artificial muscle–based robotics toward high-precision, dynamic manipulation tasks.

Technology Category

• Intelligent Robots: Manipulation
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Planning, Routing, and Scheduling: Model-Based Reasoning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Robotic wrists play a pivotal role in the functionality of industrial manipulators and humanoid robots, facilitating manipulation and grasping tasks. In recent years, there has been a growing interest in integrating artificial muscle-driven actuators for robotic wrists, driven by advancements in technology offering high energy density, lightweight construction, and compact designs. However, in the study of robotic wrists driven by artificial muscles, dynamic model-based controllers are often overlooked, despite their critical importance for motion analysis and dynamic control of robots. This paper presents a novel design of a two-degree-of-freedom (2-DOF) robotic wrist driven by twisted and coiled actuators (TCA) utilizing a parallel mechanism with a 3RRRR configuration. The proposed robotic wrist is expected to feature lightweight structures and superior motion performance while mitigating friction issues. The Lagrangian dynamic model of the wrist is established, along with a nonlinear model predictive controller (NMPC) designed for trajectory tracking tasks. A prototype of the robotic wrist is developed, and extensive experiments are conducted to validate its superior motion performance and the proposed dynamic model. Subsequently, extensive comparative experiments between NMPC and PID controller were conducted under various operating conditions. The experimental results demonstrate the effectiveness and robustness of the dynamic model-based controller in the motion control of TCA-driven robotic wrists.

Problem

• Design and control of a 2-DOF robotic wrist using twisted and coiled actuators.
• Development of a dynamic model and nonlinear predictive controller for trajectory tracking.
• Validation of lightweight design and superior motion performance through experiments.

Innovation

• 2-DOF robotic wrist with twisted and coiled actuators
• Parallel mechanism using 3RRRR configuration
• Nonlinear model predictive controller for trajectory tracking