Robust continuous motion strategy against muscle rupture using online learning of redundant intersensory networks for musculoskeletal humanoids

Kawaharazuka, Kento; Nishiura, Manabu; Toshimitsu, Yasunori; Omura, Yusuke; Koga, Yuya; Asano, Yuki; Okada, Kei; Kawasaki, Koji; Inaba, Masayuki

doi:10.1016/j.robot.2022.104067

Cited by 11 publications

(8 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results showed that the average angle error of the elbow joint was 0.12 rad. To improve security, Kawaharazuka et al (2022) discussed the use of online learning of redundant intersensory networks for muscle rupture detection, online update of the intersensory relationship considering muscle rupture, and the body control and state estimation using muscle rupture information. Although the control methods explored in the above studies have solved part problems in the hardware application of musculoskeletal robots, there are still some problems that need to be further studied, such as how to prevent local muscle tension overload accidents and improve the stability and safety.…”

Section: Introductionmentioning

confidence: 99%

“…The human arm can rapidly, flexibly, safely and robustly complete complex operation tasks with high robustness, muscle nonlinearity and multimuscle redundancy (Qiao et al , 2021; Chen and Qiao, 2021; Zhong et al , 2021; Zhou et al , 2022; Qiao et al , 2022). Arm-musculoskeletal robots have been extensively studied owing to the flexibility of their skeletal joints (such as the absence of singular positions of shoulder-ball joints) and the variable stiffness control due to from multiple antagonistic muscles (Kawaharazuka et al , 2019; Asano et al , 2017; Kozuki et al , 2012; Wittmeier et al , 2013; Zhong et al , 2022). Jantsch et al (2013) developed the simplified human upper limb with muscle tension sensors robot “ Anthrob ,” which comprised 13 compliant muscles and four degrees of freedom (DOF) joint.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm

Yuan

Fan

2023

RIA

View full text Add to dashboard Cite

Purpose This study aims to propose a novel lightweight tendon-driven musculoskeletal arm (LTDM-arm) robot with a flexible series–parallel mixed skeletal joint structure and modularized artificial muscle system (MAMS). The proposed LTDM-arm exhibits human-like flexibility, safety and operational accuracy. In addition, to improve the safety and stability of the LTDM-arm, a control method is proposed to solve local artificial muscle overload accidents. Design/methodology/approach The proposed LTDM-arm comprises seven degrees of freedom skeletons, 15 MAMSs and various sensor systems (joint sensing, muscle tension sensing, visual sensing, etc.). It retains the morphology of a human skeleton (humerus, ulna and radius) and a simplified muscle configuration. This study proposes an input saturation control with full-state constraints to reduce local artificial muscle overload accidents caused by redundant muscle tension calculations. Findings 3D circular trajectory experiments were conducted to verify the stability of the control method and the flexibility of the LTDM-arm. The results showed that the average error of the muscle length was approximately 0.35 mm (0.38%), which indicates that the proposed control scheme can make the output follow the target trajectory while ensuring constraint satisfaction. Originality/value The human arm is capable of performing compliant operations rapidly, flexibly and robustly in unstructured environments. Existing musculoskeletal arm robots lack simulations of the full morphology of the human arm and are insufficient in dexterity. However, the flexibility and safety features of the proposed LTDM-arm were consistent with that of the human arm. Therefore, this study offers a new approach for investigating the advantages of the musculoskeletal system and the concepts of muscle control.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm

Yuan

Fan

2023

RIA

View full text Add to dashboard Cite

show abstract

“…However, for highly coupled nonlinear musculoskeletal robots, suitable control schemes have not been developed to date. In addition, muscle-based controllers have certain limitations, including difficulties with stability analyses and feedback control (Wu et al , 2021; Kawaharazuka et al , 2022). Typically, muscle models are highly coupled multisegment structures, and quantifying the boundedness of variables through feedback control is often difficult.…”

Section: Introductionmentioning

confidence: 99%

“…Typically, muscle models are highly coupled multisegment structures, and quantifying the boundedness of variables through feedback control is often difficult. Furthermore, existing control methods for musculoskeletal robots are often incapable of accurately describing the dynamic uncertainties of the system or resisting unknown disturbances (Kawaharazuka et al , 2022; Han et al , 2021). In this case, ignoring the dynamic uncertainty compensation of musculoskeletal robots based on internal muscle forces leads to dynamic creep behaviors, such as the sudden relative sliding of cables under the influence of elastic deformation in real-world operations.…”

Section: Introductionmentioning

confidence: 99%

“…Second, TDMS structures are complex, and, usually, they cannot be appropriately described based on geometric models. Therefore, bridging the gap between models and actual musculoskeletal robots is an important issue to be addressed (Kawaharazuka et al, 2022;Chen and Qiao, 2020). Third, owing to the influence of environmental noise, musculoskeletal robots are inevitably disturbed (He et al, 2017; muscles participate in body movements during certain tasks, some bio-mechanists have developed computational muscle controllers (Jäntsch et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive neuromuscular control of a simplified muscle tendon-driven musculoskeletal system

Fan,

Wu,

Yuan

2023

RIA

View full text Add to dashboard Cite

Purpose This study aims to improve the muscle model control performance of a tendon-driven musculoskeletal system (TDMS) to overcome disadvantages such as multisegmentation and strong coupling. An adaptive network controller (ANC) with a disturbance observer is established to reduce the modeling error of the musculoskeletal model and improve its antidisturbance ability. Design/methodology/approach In contrast to other control technologies adopted for musculoskeletal humanoids, which use geometric relationships and antagonist inhibition control, this study develops a method comprising of three parts. (1) First, a simplified musculoskeletal model is constructed based on the Taylor expansion, mean value theorem and Lagrange–d’Alembert principle to complete the decoupling of the muscle model. (2) Next, for this simplified musculoskeletal model, an adaptive neuromuscular controller is designed to acquire the muscle-activation signal and realize stable tracking of the endpoint of the muscle-driven robot relative to the desired trajectory in the TDMS. For the ANC, an adaptive neural network controller with a disturbance observer is used to approximate dynamical uncertainties. (3) Using the Lyapunov method, uniform boundedness of the signals in the closed-loop system is proved. In addition, a tracking experiment is performed to validate the effectiveness of the adaptive neuromuscular controller. Findings The experimental results reveal that compared with other control technologies, the proposed design techniques can effectively improve control accuracy. Moreover, the proposed controller does not require extensive considerations of the geometric and antagonistic inhibition relationships, and it demonstrates anti-interference ability. Originality/value Musculoskeletal robots with humanoid structures have attracted considerable attention from numerous researchers owing to their potential to avoid danger for humans and the environment. The controller based on bio-muscle models has shown great performance in coordinating the redundant internal forces of TDMS. Therefore, adaptive controllers with disturbance observers are designed to improve the immunity of the system and thus directly regulate the internal forces between the bio-muscle models.

show abstract

Variable end-point viscoelasticity control for a musculoskeletal redundant arm

et al. 2023

View full text Add to dashboard Cite

Robust continuous motion strategy against muscle rupture using online learning of redundant intersensory networks for musculoskeletal humanoids

Cited by 11 publications

References 30 publications

Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm

Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm

Adaptive neuromuscular control of a simplified muscle tendon-driven musculoskeletal system

Variable end-point viscoelasticity control for a musculoskeletal redundant arm

Contact Info

Product

Resources

About