Long-time Self-body Image Acquisition and its Application to the Control of Musculoskeletal Structures
arXiv:2404.05293 · doi:10.1109/LRA.2019.2923968
Abstract
The tendon-driven musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex muscle and bone structures is difficult and conventional model-based controls cannot realize intended movements. Therefore, a learning control mechanism that acquires nonlinear relationships between joint angles, muscle tensions, and muscle lengths from the actual robot is necessary. In this study, we propose a system which runs the learning control mechanism for a long time to keep the self-body image of the musculoskeletal humanoid correct at all times. Also, we show that the musculoskeletal humanoid can conduct position control, torque control, and variable stiffness control using this self-body image. We conduct a long-time self-body image acquisition experiment lasting 3 hours, evaluate variable stiffness control using the self-body image, etc., and discuss the superiority and practicality of the self-body image acquisition of musculoskeletal structures, comprehensively.
Accepted at IEEE Robotics and Automation Letters, 2019
References in corpus (2)
Cited by in corpus (26)
- Component Modularized Design of Musculoskeletal Humanoid Platform Musashi to Investigate Learning Control Systems
- Musculoskeletal AutoEncoder: A Unified Online Acquisition Method of Intersensory Networks for State Estimation, Control, and Simulation of Musculoskeletal Humanoids
- Object Recognition, Dynamic Contact Simulation, Detection, and Control of the Flexible Musculoskeletal Hand Using a Recurrent Neural Network with Parametric Bias
- Robust Continuous Motion Strategy Against Muscle Rupture using Online Learning of Redundant Intersensory Networks for Musculoskeletal Humanoids
- Toward Autonomous Driving by Musculoskeletal Humanoids: A Study of Developed Hardware and Learning-Based Software
- Imitation Learning with Additional Constraints on Motion Style using Parametric Bias
- Estimation and Control of Motor Core Temperature with Online Learning of Thermal Model Parameters: Application to Musculoskeletal Humanoids
- Adaptive Robotic Tool-Tip Control Learning Considering Online Changes in Grasping State
- Reflex-based Motion Strategy of Musculoskeletal Humanoids under Environmental Contact Using Muscle Relaxation Control
- Hardware Design and Learning-Based Software Architecture of Musculoskeletal Wheeled Robot Musashi-W for Real-World Applications
- Self-Body Image Acquisition and Posture Generation with Redundancy using Musculoskeletal Humanoid Shoulder Complex for Object Manipulation
- Design Optimization of Musculoskeletal Humanoids with Maximization of Redundancy to Compensate for Muscle Rupture
- Adaptive Body Schema Learning System Considering Additional Muscles for Musculoskeletal Humanoids
- Exceeding the Maximum Speed Limit of the Joint Angle for the Redundant Tendon-driven Structures of Musculoskeletal Humanoids
- Learning of Balance Controller Considering Changes in Body State for Musculoskeletal Humanoids
- Modification of muscle antagonistic relations and hand trajectory on the dynamic motion of Musculoskeletal Humanoid
- Applications of Stretch Reflex for the Upper Limb of Musculoskeletal Humanoids: Protective Behavior, Postural Stability, and Active Induction
- Online Learning of Danger Avoidance for Complex Structures of Musculoskeletal Humanoids and Its Applications
- Realization of Seated Walk by a Musculoskeletal Humanoid with Buttock-Contact Sensors From Human Constrained Teaching
- Automatic Grouping of Redundant Sensors and Actuators Using Functional and Spatial Connections: Application to Muscle Grouping for Musculoskeletal Humanoids
- CubiXMusashi: Fusion of Wire-Driven CubiX and Musculoskeletal Humanoid Musashi toward Unlimited Performance
- Characteristics, Management, and Utilization of Muscles in Musculoskeletal Humanoids: Empirical Study on Kengoro and Musashi
- Stability Recognition with Active Vibration for Bracing Behaviors and Motion Extensions Using Environment in Musculoskeletal Humanoids
- Motion Modification Method of Musculoskeletal Humanoids by Human Teaching Using Muscle-Based Compensation Control
- PIMBS: Efficient Body Schema Learning for Musculoskeletal Humanoids with Physics-Informed Neural Networks
- Online Learning Feedback Control Considering Hysteresis for Musculoskeletal Structures