With the background of research on materials laboratory automation, this study aims to construct an automation system for measuring dielectric property, which is an electrical property of materials. The automation system is composed of the combination of a manipulation by a force-sensing robot and a control system for the measurement instrument. As challenges for the automation system, we worked on stabilizing a polymer film placement during insertion into the measurement instrument, implementing a communication control system between different platforms, and constructing a polymer film transfer environment. In the measurement experiment using the automation system, it was confirmed that the dielectric properties could be measured as well as that of a human.

Self-healing function is a promising approach for damage management of high-load robot applications such as legged robots. Although the function is getting major in soft robotics, its application to life-sized "stiff" robots is of relatively minor interest. Although the authors have devised several self-healing tensile modules for tendon-driven robots, the design guideline to satisfy the large load endurance and large stroke is still unclear. The paper focuses on the parametric design for unleaked liquid-assisted healing of low melting point alloy structure. The method was validated with a benchtop module test. Moreover, the module enabled tendon-driven monopod testbed to perform squat motion three times after the landing impact fracture and the self-healing sequence, which was never accomplished.

We have implemented a force-based operational space controller on a physical musculoskeletal humanoid robot arm. The controller calculates muscle activations based on a biomimetic Hill-type muscle model. We propose a method to include the joint torque nullspace in the optimization process, which enables the robot to exploit the nullspace to gradually lower its overall muscle activation. We have verified in experiments that it can react compliantly to external disturbances while retaining its operational space task.

Musculoskeletal humanoids have various biomimetic advantages, and the redundant muscle arrangement allowing for variable stiffness control is one of the most important. In this study, we focus on one feature of the redundancy, which enables the humanoid to keep moving even if one of its muscles breaks, an advantage that has not been dealt with in many studies. In order to make the most of this advantage, the design of muscle arrangement is optimized by considering the maximization of minimum available torque that can be exerted when one muscle breaks. This method is applied to the elbow of a musculoskeletal humanoid Musashi with simulations, the design policy is extracted from the optimization results, and its effectiveness is confirmed with the actual robot.

The flexible under-actuated musculoskeletal hand is superior in its adaptability and impact resistance. On the other hand, since the relationship between sensors and actuators cannot be uniquely determined, almost all its controls are based on feedforward controls. When grasping and using a tool, the contact state of the hand gradually changes due to the inertia of the tool or impact of action, and the initial contact state is hardly kept. In this study, we propose a system that trains the predictive network of sensor state transition using the actual robot sensor information, and keeps the initial contact state by a feedback control using the network. We conduct experiments of hammer hitting, vacuuming, and brooming, and verify the effectiveness of this study.

It is necessary to use not only foot but also hand, knee and other body parts to support body weight for locomotion in uneven terrain. Such multi-contact motion planning is an important research topic including lots of previous works; however, a problem of computational speed of planning is still remaining. In this paper, we propose a learning-based algorithm to speed up the planning. The algorithm reduces replanning of contact states by learning an evaluation function of key pose to reach goal. We investigated the learning performance by comparing three neural network configurations and two activation function. This research aims at achieving robust robotics system in unknown environments.

The musculoskeletal humanoid has various biomimetic benefits, and the redundant muscle arrangement is one of its most important characteristics. This redundancy can achieve fail-safe redundant actuation and variable stiffness control. However, there is a problem that the maximum joint angle velocity is limited by the slowest muscle among the redundant muscles. In this study, we propose two methods that can exceed the limited maximum joint angle velocity, and verify the effectiveness with actual robot experiments.

The musculoskeletal humanoid has various biomimetic benefits, and it is important that we can embed and evaluate human reflexes in the actual robot. Although stretch reflex has been implemented in lower limbs of musculoskeletal humanoids, we apply it to the upper limb to discover its useful applications. We consider the implementation of stretch reflex in the actual robot, its active/passive applications, and the change in behavior according to the difference of parameters.

In this research, we have taken a biomimetic approach to the control of musculoskeletal humanoids. A controller was designed based on the motor directional tuning phenomenon seen in the motor cortex of primates. Despite the simple implementation of the control scheme, complex coordinated movements such as reaching for target objects with its upper body was achieved, and is demonstrated in the accompanying video. The controller does not require an internal model, and instead constantly observes its body in relation to the external world to update motor commands. We claim that such an embodied approach to the control of musculoskeletal robots will be able to effectively take advantage of their complex bodies to achieve motion.

To develop Musashi as a musculoskeletal humanoid platform to investigate learning control systems, we aimed for a body with flexible musculoskeletal structure, redundant sensors, and easily reconfigurable structure. For this purpose, we develop joint modules that can directly measure joint angles, muscle modules that can realize various muscle routes, and nonlinear elastic units with soft structures, etc. Next, we develop MusashiLarm, a musculoskeletal platform composed of only joint modules, muscle modules, generic bone frames, muscle wire units, and a few attachments. Finally, we develop Musashi, a musculoskeletal humanoid platform which extends MusashiLarm to the whole body design, and conduct several basic experiments and learning control experiments to verify the effectiveness of its concept.

The musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex flexible body is difficult. Although we have developed an online acquisition method of the nonlinear relationship between joints and muscles, we could not completely match the actual robot and its self-body image. When realizing a certain task, the direct relationship between the control input and task state needs to be learned. So, we construct a neural network representing the time-series relationship between the control input and task state, and realize the intended task state by applying the network to a real-time control. In this research, we conduct accelerator pedal control experiments as one application, and verify the effectiveness of this study.

Self-healing robotics has been of considerable interest. We believe the function will have a major role in legged robots as a typical high-load application of robotics. Some pioneering works have been ongoing on self-healing soft robots. However, the development of large load self-healing component and its system integration with a life-sized legged robot is a challenging task. This study is to try the problem by a constructing self-healing component oriented for facilitated investigation. Proposed part enhances visibility and manufacturing by specializing tension transmission system. The developed module was evaluated by several experiments. First, healing visualization experiment was conducted to evaluate healing progress. In addition, the module's strength was tested using a motor-driven tendon module previously developed in our laboratory. Results of these experiments suggested that the stirring process have a major role in performing self-healing behaviour. Finally, we conducted a preliminary experiment on a tendon-driven legged robot. The experiment demonstrated that the module functioned in a real robot once.

To realize a robust automobile driving behavior of musculoskeletal tendon-driven humanoids, we developed a six-axis force measurement module with a core-shell structure. This sensor enables space saving, high load capacity and wholebody sensing at the same time. By developing a foot unit incorporating a core-shell structural force sensor on its toe, we realized behaviors of depressing a pedal and recovering from foot slipping during the depressing with a lifesized musculoskeletal humanoid ”Musashi”.

Tendon-driven musculoskeletal humanoids have many benefits in terms of the flexible spine, multiple degrees of freedom, and variable stiffness. At the same time, because of its body complexity, there are problems in controllability. First, due to the large difference between the actual robot and its geometric model, it cannot move as intended and large internal muscle tension may emerge. Second, movements which do not appear as changes in muscle lengths may emerge, because of the muscle route changes caused by softness of body tissue. To solve these problems, we construct two models: ideal joint-muscle model and muscle-route change model, using a neural network. We initialize these models by a man-made geometric model and update them online using the sensor information of the actual robot. We validate that the tendon-driven musculoskeletal humanoid Kengoro is able to obtain a correct self-body image through several experiments.

Human hands can not only grasp objects of various shape and size and manipulate them in hands but also exert such a large gripping force that they can support the body in the situations such as dangling a bar and climbing a ladder. On the other hand, it is difficult for most robot hands to manage both. Therefore in this paper we developed the hand which can grasp various objects and exert large gripping force. To develop such hand, we focused on the thumb CM joint with wide range of motion and the MP joints of four fingers with the DOF of abduction and adduction. Based on the hand with large gripping force and flexibility using machined spring, we applied above mentioned joint mechanism to the hand. The thumb CM joint has wide range of motion because of the combination of three machined springs and MP joints of four fingers have variable rigidity mechanism instead of driving each joint independently in order to move joint in limited space and by limited actuators. Using the developed hand, we achieved the grasping of various objects, supporting a large load and several motions with an arm.

The human forearm is composed of two long, thin bones called the radius and the ulna, and rotates using two axle joints. We aimed to develop a forearm based on the body proportion, weight ratio, muscle arrangement, and joint performance of the human body in order to bring out its benefits. For this, we need to miniaturize the muscle modules. To approach this task, we arranged two muscle motors inside one muscle module, and used the space effectively by utilizing common parts. In addition, we enabled the muscle module to also be used as the bone structure. Moreover, we used miniature motors and developed a way to dissipate the motor heat to the bone structure. Through these approaches, we succeeded in developing a forearm with a radioulnar joint based on the body proportion, weight ratio, muscle arrangement, and joint performance of the human body, while keeping maintainability and reliability. Also, we performed some motions such as soldering, opening a book, turning a screw, and badminton swinging using the benefits of the radioulnar structure, which have not been discussed before, and verified that Kengoro can realize skillful motions using the radioulnar joint like a human.

Human can not only support their body during standing or walking, but also support them by hand, so that they can dangle a bar and others. But most humanoid robots support their body only in the foot and they use their hand just to manipulate objects because their hands are too weak to support their body. Strong hands are supposed to enable humanoid robots to act in much broader scene. Therefore, we developed new life-size five-fingered hand that can support the body of life-size humanoid robot. It is tendon-driven and underactuated hand and actuators in forearms produce large gripping force. This hand has flexible joints using machined springs, which can be designed integrally with the attachment. Thus, it has both structural strength and impact resistance in spite of small size. As other characteristics, this hand has force sensors to measure external force and the fingers can be flexed along objects though the number of actuators to flex fingers is less than that of fingers. We installed the developed hand on musculoskeletal humanoid “Kengoro” and achieved two self-weight supporting motions: push-up motion and dangling motion.

We propose a human mimetic foot structure for musculoskeletal humanoids. We designed the foot structure by inspiring from human foot abilities of the multi-bone connected structure for flexibility and the distributed force sensor system. The foot has multi-DOFs structure including toe DOF that is composed of fingers. The distributed force sensing system is composed of 12 an-axis force sensors. In order to demonstrate those effectiveness, we implement the foot into musculoskeletal humanoid Kengoro and conduct several experiments. As a result, we confirmed effectiveness of the foot from tiptoe motion and balancing behavior by utilizing the foot characteristics.

In this paper we propose a novel method to utilize the skeletal structure not only for supporting force but for releasing heat by latent heat.

We propose a sensor-driver integrated muscle module by integrating necessarily components for tendon-driven robot which is likely to complicate. The module has abilities of high-tension measurability and flexible tension control. In order to achieve flexible tension control, we developed the new tension measurement mechanism with high-tension measurability and the new motor driver which enables current based motor control. We demonstrate the tension control ability of the module by several experiments. Furthermore, utilizing the module advantage of design facilitation, we made two types of tendon-driven robots and confirmed effectiveness of the module.

The main goal of this paper is to design and evaluate a spine structure which withstands various motions. The structure around the neck has a prevailing importance since it is involved in various motions of the upper half of the body. The new design method we introduce essentially shows how to design all 7 cervical vertebrae (the part of spine in the neck) in a limited space, actuated by the wires winded around the motors. Then we show the muscle arrangements around the upper half of the spine. More specifically, we make use of a so called planar muscle mechanism. An abduction experiment which requires great force around the spine is made to show its stability. Finally, we show a variable stiffness system which enables the spine to resist an impulsive force. We have tested the system in the situation of whiplash injury which is a case of extreme external forces which can occur in car crash accidents. As such we have evaluated the strength of the design and the viability of our robot to act as a human body simulator.

Human knee joint has a yaw-axis rotational DOF and a locking mechanism called screw-home mechanism. We focus on this mechanism and implement it to a musculoskeletal humanoid through hardware design. The importance of developing a knee joint with screw-home mechanism is that such a joint is capable of working yaw-axis properly and generating enough pitch joint torque for supporting whole body motion. In this paper, as an evaluation of our developed knee joint, we first checked the moment arm of the yaw rotational axis of the knee. Moreover, we also checked the yaw angle displacement during squat motion. From these results, we confirmed that the mechanism worked properly. Second, in order to check whether enough pitch joint torque is generated during movement, we conducted several experiments with whole body motions such as squatting. Lastly, as unique and integrated motions that involve the use of yaw DOF derived from the mechanism, we tested knee joint Open-Close, Right-to-Left and whole body twist squat motion. Our results demonstrated the feasibility of musculoskeletal humanoids with screw-home mechanism and showed that we have achieved humanlike twisting motion.

This paper presents a design methodology for humanoid upper limb based on human anatomy. Kenshiro is a full body tendon driven humanoid robot and is designed from the data of average 14 year old Japanese boy. The design of his upper limb is realizing detail features of muscles, bones and the adhesive relation of the two. Human mimetic design is realized by focusing on the fact that joints are being stabled by muscles winding around the bones, and by accurately mimicking the bone shape this was enabled. In this paper we also introduce details of mechanical specifications of the upper limb. By having muscles, bones, and joint structures based on human anatomy, Kenshiro can move flexibly. The use as human body simulator can be expected by measuring sensor data which can correspond to biological data.

In order to know human dynamics, humanoid as a human body simulator is increasing its importance. Such humanoid is expected to have human musculoskeletal structure as close as possible. From this viewpoint, we are trying to create new musculoskeletal humanoid which has detailed human imitating structure, such as bi-articular muscle, muscle arrangement, joint structure and so on. In this paper, we address the design of lower thigh. The concepts of the thigh include leg configuration, new knee joint and link, and artificial muscle arrangements, especially knee joint structure imitating human flexible motion. The knee joint has yaw axis DOF and its locking mechanism which is usually simplified in robotics. Finally, we conduct extension, flexion and rotation as basic experiment to confirm the joint characteristics. Also, we conduct rotation experiment in the ground state to confirm the contribution of yaw axis DOF for human-like motion.

To design a robot with humanlike body structure, this paper presents a design methodology for a humanoid upper limb by tendon driven system. We newly designed an upper limb and rib cage like thorax for a musculoskeletal humanoid robot, based on the knowledge of anatomy. The robot consists of muscle, bone, and joint structure based on human and is expected to move flexibly and dynamically. This paper describes how to design such an upper limb and proposes the key mechanical design points, which is “rib surface thorax”, “muscle cushion”, “planar muscle”, and “open type ball joint”. To show that these mechanisms is effective in making a musculoskeletal humanoid robot, we examine the motion range of the robot. One of our goals is to enable robots to do the same movements as humans do through mimicking the human body structure, finding some important elements of human nature. This robots explained in this paper is the prototype for a new life size robot “Kenshiro” project.