Soichi Ookubo

A sensor-driver integrated muscle module with high-tension measurability and flexibility for tendon-driven robots

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.

Human mimetic musculoskeletal humanoid Kengoro toward real world physically interactive actions

We have been developing human mimetic musculoskeletal humanoids from the view point of human-inspired design approach. Kengoro is our latest version of musculoskeletal humanoid designed to achieve physically interactive actions in real world. This study presents the design concept, body characteristics, and motion achievements of Kengoro. In the design process of Kengoro, we adopted the novel idea of multifunctional skeletal structures to achieve both humanoid performance and humanlike proportions. We adopted the sensor-driver integrated muscle modules for improved muscle control. In order to demonstrate the effectiveness of these body structures, we conducted several preliminary movements using Kengoro.

Learning nonlinear muscle-joint state mapping toward geometric model-free tendon driven musculoskeletal robots

To control a musculoskeletal tendon-driven robot we propose a novel method to learn musculoskeletal nonlinear bidirectional mapping between muscle length and posture (joint angle) from a real musculoskeletal robot. We show the nonlinear musculoskeletal mapping from joint angle to muscle length can be learned as a linear combination of simple nonlinear functions. This formulation can be extended to posture estimation (mapping from muscle length to joint angle) by EKF (Extened Kalman Filter) and torque estimation by differentiation in a musculoskeletal robot. In this paper, we applied the method to tendon driven musculoskeletal robots and verified the validity.

A joint-space controller based on redundant muscle tension for multiple DOF joints in musculoskeletal humanoids

To achieve contact tasks with musculoskeletal humanoids, adaptive motion by muscle tension control and robustness against actuator malfunction is important. In this paper, we develop a tension-based joint-space controller for musculoskeletal multiple DOF joints. Joint angle estimation is integrated with the controller, enabling application to spherical joints and spine structure whose joint angle cannot be directly measured. Furthermore, by utilizing the muscle redundancy, a fault tolerant controller is enabled. For evaluation we develop the head and neck of the musculoskeletal humanoid “Kengoro”. We demonstrate by motion generating experiments that the controller is valid and that joint torque estimation is improved compared with a previous controller based on muscle length. Toward an application for contact tasks, we show that contact detection on unknown environments is achieved utilizing the estimated joint torque.

Development of musculoskeletal spine structure that fulfills great force requirements in upper body kinematics

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.

Spine Balancing Strategy Using Muscle ZMP on Musculoskeletal Humanoid Kenshiro

In this paper, we propose a new balancing strategy for musculoskeletal humanoids by using their redundant musculoskeletal structures. This strategy is based on the idea of muscle Zero Moment Point(ZMP) and involves the use of a balance stabilizer utilizing the spine. The muscle ZMP is a stabilization indicator instead of a normal ZMP that is computed from 6DOF force sensors installed on robots’ foot. In order to compute the muscle ZMP, we use the joint torques obtained from muscle tensions. The spine stabilizer compensates for the COG displacement of the whole-body by utilizing the spine movements. Further, we confirm the effectiveness of the proposed strategy by demonstrating several balancing motions of Kenshiro, a musculoskeletal humanoid.

Human mimetic foot structure with multi-DOFs and multi-sensors for musculoskeletal humanoid Kengoro

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.

NanoBridge-Based FPGA in High-Temperature Environments

The authors demonstrate a field-programmable gate array (FPGA) based on NanoBridge, a novel resistive-change switch. NanoBridge, which is integrated in the back end of line (BEOL), features a high on/off conductance ratio, weak temperature dependence of its resistance, nonvolatility, endurance against soft errors, and a small footprint. In place of static RAM (SRAM) and a pass transistor, NanoBridge is utilized as a configuration switch in the FPGA. In this article, the authors evaluate the NanoBridge-based FPGA (NB-FPGA) for applications in harsh environments. Specifically, they implemented NB-FPGA in a humanoid robot and compared its performance with that of the conventional FPGA. Results showed that NB-FPGA exhibits small variation in performance over a wide range of temperature, from −55 to 150 °C, and has high immunity for fluctuations in the power supply voltage.