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Construction of Musculoskeletal Simulation for Shoulder Complex with Ligaments and Its Validation via Model Predictive Control

Yuta Sahara, Akihiro Miki, Yoshimoto Ribayashi, Shunnosuke Yoshimura, Kento Kawaharazuka, Kei Okada, Masayuki Inaba

TL;DR

This work advances shoulder biomechanics for robotics by building a detailed musculoskeletal model of the shoulder complex that includes ligaments and 40 muscles, simulated in MuJoCo with Hill-type muscle dynamics. It employs model predictive control to demonstrate that ligaments stabilize the initial raising motion and that appropriate distribution of maximum muscle forces yields more uniform muscle loading. Through experiments comparing with/without ligaments and estimated versus averaged muscle strengths, it shows the critical roles of soft tissues and force distribution in joint stability and posture. The resulting framework enables rigorous analysis and optimization of shoulder movement for sports, rehabilitation, and musculoskeletal humanoid robotics.

Abstract

The complex ways in which humans utilize their bodies in sports and martial arts are remarkable, and human motion analysis is one of the most effective tools for robot body design and control. On the other hand, motion analysis is not easy, and it is difficult to measure complex body motions in detail due to the influence of numerous muscles and soft tissues, mainly ligaments. In response, various musculoskeletal simulators have been developed and applied to motion analysis and robotics. However, none of them reproduce the ligaments but only the muscles, nor do they focus on the shoulder complex, including the clavicle and scapula, which is one of the most complex parts of the body. Therefore, in this study, a detailed simulation model of the shoulder complex including ligaments is constructed. The model will mimic not only the skeletal structure and muscle arrangement but also the ligament arrangement and maximum muscle strength. Through model predictive control based on the constructed simulation, we confirmed that the ligaments contribute to joint stabilization in the first movement and that the proper distribution of maximum muscle force contributes to the equalization of the load on each muscle, demonstrating the effectiveness of this simulation.

Construction of Musculoskeletal Simulation for Shoulder Complex with Ligaments and Its Validation via Model Predictive Control

TL;DR

This work advances shoulder biomechanics for robotics by building a detailed musculoskeletal model of the shoulder complex that includes ligaments and 40 muscles, simulated in MuJoCo with Hill-type muscle dynamics. It employs model predictive control to demonstrate that ligaments stabilize the initial raising motion and that appropriate distribution of maximum muscle forces yields more uniform muscle loading. Through experiments comparing with/without ligaments and estimated versus averaged muscle strengths, it shows the critical roles of soft tissues and force distribution in joint stability and posture. The resulting framework enables rigorous analysis and optimization of shoulder movement for sports, rehabilitation, and musculoskeletal humanoid robotics.

Abstract

The complex ways in which humans utilize their bodies in sports and martial arts are remarkable, and human motion analysis is one of the most effective tools for robot body design and control. On the other hand, motion analysis is not easy, and it is difficult to measure complex body motions in detail due to the influence of numerous muscles and soft tissues, mainly ligaments. In response, various musculoskeletal simulators have been developed and applied to motion analysis and robotics. However, none of them reproduce the ligaments but only the muscles, nor do they focus on the shoulder complex, including the clavicle and scapula, which is one of the most complex parts of the body. Therefore, in this study, a detailed simulation model of the shoulder complex including ligaments is constructed. The model will mimic not only the skeletal structure and muscle arrangement but also the ligament arrangement and maximum muscle strength. Through model predictive control based on the constructed simulation, we confirmed that the ligaments contribute to joint stabilization in the first movement and that the proper distribution of maximum muscle force contributes to the equalization of the load on each muscle, demonstrating the effectiveness of this simulation.
Paper Structure (11 sections, 2 equations, 15 figures, 3 tables)

This paper contains 11 sections, 2 equations, 15 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Configuration of the musculoskeletal model of the shoulder complex
  3. Linked structure of the skeleton
  4. Representation and placement of ligaments
  5. Representation and placement of muscles
  6. Position control by model predictive control
  7. Experiments with position control
  8. Movement experiment by position control of elbow tip
  9. Raising movement experiment with and without ligaments
  10. Raising movement experiment with estimated and averaged maximum muscle force
  11. Conclusion

Figures (15)

  • Figure 1: Overview of the proposed musculoskeletal model.
  • Figure 2: Ligaments. The yellow wire on right figure is the ligament.
  • Figure 3: Muscles. The red wire on right figure is the muscle.
  • Figure 5: Position control of the proposed musculoskeletal model with MPC. The two yellow balls are the target positions. The muscles are controlled to bring the tip of the humerus closer to the target position.
  • Figure 6: Abduction
  • ...and 10 more figures