Estimation and Control of Motor Core Temperature with Online Learning of Thermal Model Parameters: Application to Musculoskeletal Humanoids

Abstract

The estimation and management of motor temperature are important for the continuous movements of robots. In this study, we propose an online learning method of thermal model parameters of motors for an accurate estimation of motor core temperature. Also, we propose a management method of motor core temperature using the updated model and anomaly detection method of motors. Finally, we apply this method to the muscles of the musculoskeletal humanoid and verify the ability of continuous movements.

Accepted at IEEE Robotics and Automation Letters

References in corpus (4)

• On the difficulty of training Recurrent Neural Networks
• Component Modularized Design of Musculoskeletal Humanoid Platform Musashi to Investigate Learning Control Systems
• Long-time Self-body Image Acquisition and its Application to the Control of Musculoskeletal Structures
• Human Mimetic Forearm Design with Radioulnar Joint using Miniature Bone-Muscle Modules and Its Applications

Cited by in corpus (3)

• Hardware Design and Learning-Based Software Architecture of Musculoskeletal Wheeled Robot Musashi-W for Real-World Applications
• Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids
• Soft robotic shell with active thermal display