The humanoid robot that can transform itself into a form according to its purpose requires whole-body motions with complex contact state transitions such as recovery from a fall and transition to the target form. To make the robot behavior in simulations closer to that in the real world for planning complex target trajectories, we need a platform that can measure the body stiffness during the motion and verify its application without being damaged by repeated motions that are prone to tipping over. In this study, we propose a small, inexpensive, and robust humanoid-vehicle transformer platform with redundant sensors and a low rigidity multi degree-of-freedom body and observe the effects of body deflection and internal forces during whole-body posture transition. By comparing the results obtained from experiments in several environments with different friction and from the simulator using a rigid body model, we were able to verify the influence of body flexibility on whole-body motion and the relationship between deflection and wrench observed by redundant sensors and movement failure.

We developed a method to enable a humanoid robot to carry stacked boxes. In order to transport objects efficiently, it is necessary to carry multiple objects at the same time, but in previous studies, humanoid robots have only been able to carry a single object. When a humanoid robot carries stacked boxes, the robot drops boxes when the positional relationship between un-grasped boxes changes. The causes for dropping the boxes can be divided into sudden changes attributed to robot making turns or losing balance, and the accumulation of small changes that occur because of the impact of landing while walking. We propose a method that prevents sudden changes in the stacked boxes by smoothing the hand trajectory and modifying the misalignment by tilting or shaking the entire stack. We verify the effectiveness of proposed method for enabling a humanoid robot to carry stacked boxes through experiments using a simulator and an actual robot.

In this work, we propose a system for humanoid robot fast motions. When a humanoid robot performs a motion such as a tennis forehand stroke motion, a whole-body fast motion in reaction to visual information is required. There are three problems to tackle. (1) Motion is desired to be quick. (2) Real-time visual processing considering visual noises is needed. (3) Real-time joint angle modification with balance keeping is needed. To solve the problem (1), we used an offline optimization system to enhance the motion speed. To solve the problem (2), we implement a ball trajectory prediction algorithm using the Extended Kalman Filter (EKF). To solve the trade-off between (1) and (3), we propose an offline optimization condition with an estimated balance margin. By using these methods, we achieved a non-step tennis forehand stroke motion with a humanoid robot by predicting a ball's trajectory with stereo cameras on the robot's head.

For mitigating joint impact torques, researchers have reduced joint stiffness by series elastic actuators, reflected inertia by low gear ratios, and friction torque from drive-trains. However, these impact mitigation methods may impair the control performance of contact forces or may increase motor and robot mass. This paper proposes a design method for achieving a balance between impact mitigation performance and force control fidelity. We introduce an inertia-to-square-torque ratio as a new index for integrating the parameters of torque generation (motor continuous torque limits, gear ratios, etc.) and the parameters of impact mitigation (joint stiffness, reflected inertia, etc.). In the process, we make a hypothesis that a motor mass is negatively correlated with the ratio. Based on the hypothesis, we calculate a joint breakdown region of impact torques, joint stiffnesses, and motor masses. Finally, we decide the drive-train specifications of JAXON3-P and demonstrate that the proposed method provides high impact mitigation and force control capabilities through several experiments including the jumping motion of 0.3 m COG height.

This paper describes basic implementation of an embedded controller board based on a hybrid architecture equipped with an Intel FPGA SoC and an NVIDIA GPU SoC. Embedded distributed network involving motor-drivers or other embedded boards is constructed with low-latency optical transmission link. The central controller for high-level motion planning is connected via Gigabit Ethernet. The controller board with the hybrid architecture provides lower-latency feedback control performance. Computing performance of the FPGA SoC, the GPU SoC, and the central controller is evaluated by computation time of matrix multiplication. Then, the total feedback latency is estimated to show the performance of the hybrid architecture.

In this paper, we propose walking balance control based on Caputurability. The proposed method consists of five strategies: (i) moving Zero Moment Point (ZMP) in the support polygon (ii) landing position modification (iii) landing timing modification (iv) angular momentum control (v) falling detection and fall control. Walking pattern generation calculates the ZMP so that the Capture Point (CP) reaches the position of the supporting foot at the end of the double support phase. Owing to the asymmetry of the reachable landing region, landing timing modification is different in the sagittal and lateral planes, and the step time is extended in the lateral plane depending on the direction of disturbances. The torque around the center of gravity to avoid falling is realized through whole-body inverse kinematics with constraints on the angular momentum. In addition, we propose falling detection considering the reachable landing region. We verified the effectiveness of the proposed method through experiments in which the biped robot was disturbed by pushing during tether-free walking. The robot could prevent breakdown by detecting possible falling and performed knee bending motions to suppress damage.

We present a torque controller for humanoid robot's arm and a method to execute heavy-load tasks under that controller. Torque control of arms can reduce the joint load when an impulsive force is applied to the robot's hand. This feature is important for robots that will work among many humans or obstacles because accidental collisions may happen in such situations. We also developed a static force filter for force sensors at the end-effectors. This filter is utilized for the compensation for the static reaction force during heavy-load tasks. A life-sized humanoid robot JAXON digs soil with a shovel and carries soil with a wheelbarrow using our proposed controller.

In order to achieve tasks in the real world environment, humanoid robots have motors and reduction drives optimized in relation to weight and size for providing the necessary torque and angle speed. Therefore, having torque or angle speed outside of the predicted range will usually cause the task to fail. In this research, we propose a joint module with a two-stage transmission mechanism during driving and a joint locking mechanism during non-driving so that the appropriate torque and joint speed can be attained during the task. By applying the joint module to a tricycle type robot and switching the driving state during the task execution, we were able to both reduce the motor load when lifting heavy objects at driving time and keep high rigidity of the joint at non-driving time.

Humanoid robots are expected to conduct tasks on behalf of humans in places such as a disaster scattered environment. Although humanoid robots have potentials to walk on uneven ground unlike wheeled robots, it is difficult to reach a given destination without falling down based on only visual information. In this paper, to reach the destination safely, we propose the autonomous safe locomotion system applying vision and sole reaction force to the footstep planning. Considering force information in addition to visual information, the robot can plan a path avoiding unstable footholds. The planned path is safer than a path which is planned based on only visual information. In our system, the robot checks if the foothold is safe or not by the foothold ascertainment motion. In addition to that, the robot saves the results of the motion to the database with the foothold label given by the visual classifier. To judge foothold safety, stiffness of the foothold is estimated from the reaction force and stepping amount. We propose the system considering these requirements for safe locomotion for bipedal robots and show experimental results using a real bipedal robot CHIDORI.

In this paper, we propose novel methods suitable for online real time whole body master-slave control with real life-sized humanoid robot. We conducted some dynamic whole body master-slave experiment with life-sized humanoid robot, and we achieved speedier and flexible master-slave operation compared to conventional study. Conventionally, master-slave operations with humanoid robots were available with only the upper body of the humanoid robot, and the COM movement was limited to be static. In our previous study, we introduced LIP model based restrictions to ensure the balance stability. In this study, we extend the safety restrictions by introducing foot landing delay prediction and trajectory smoothing method suitable for real robot. We conducted master-slave tennis swing experiment and high kick motion experiment with life-sized humanoid robot “JAXON”, and we evaluated the effectiveness of our proposed methods and system.

In this paper, we introduce a novel robotic prosthetic knee as shown in Fig. 1 (named as SuKnee) with variable transmission mechanism that could vary transmission ratio while knee angle varies during ambulation activities. A slider crank mechanism is utilized to transform linear motion of series elastic actuator to rotary motion of knee joint. And it contributes to variable transmission ratio with knee angle, which help obtain desired speed variation and torque output in different activities in one mechanism. This feature could uniquely give the SuKnee both: the torque necessary to assist with standing up from a chair and the speed necessary to swing the leg forward during walking. The knee has an active mode, where it operates with batteries and is capable of providing external power, and a passive mode, behaving like a passive prosthesis. Preliminary tests have been performed by a transfemoral amputee and SuKnee could provide user with power to assist walking on level ground and standing up from a chair. And a passive mode test shows it could work like passive prosthesis after battery exhaustion.

Comparing to IK (Inverse Kinematics) based motion control, joint-space motion control is more advantageous in terms of not being restricted by kinematics singularity problem. In this paper, we start with SIMBICON (Simple Biped Locomotion Control) based controller, a joint-space motion control method, extend it for enhancing walking's robustness and versatility. We propose a motion optimization method considering walking robustness, desired walking velocity and energy efficient minimization for walking motion generation. This method enables us to achieve human-like walking motion, which has stretched-knee posture and robust to large push disturbances. We also apply our proposed method to a life-sized biped robot and validate its effectiveness with push recovery and walking on unknown debris experiments.

Currently, most of commercially available ankle foot prosthesis are passive, which don't exhibit appropriate biomechanics during walking and could not adapt to dynamic property of able-bodied walking. In this paper, we present a novel robotic ankle foot prosthesis with variable transmission series elastic actuator (SEA). Slider crank mechanism is applied to transform linear motion of series elastic actuator to rotary motion of ankle foot joint. And this could contribute to variable transmission ratio while ankle angle varies. Because of variable transmission ratio, ankle joint torque is increasing while ankle angle is flexed from plantar flexion to dorsiflexion, whose feature has similar increase trend with human's ankle joint torque-angle relationship, and exhibits an appropriate characteristic for developing robotic ankle foot prosthesis. Larger torque could be obtained in powered plantar flexion, and this indicates that variable transmission mechanism would help reduce required motor torque compared with traditional mechanism. Energy stored in springs of series elastic actuator contribute a torque to powered plantar flexion. Preliminary experiments with a transtibial amputee and a transferomal amputee have been performed to test the prototype.

In this study, we propose a novel method to operate whole body of a humanoid robot, which also includes both feet, dynamically and safely with the master-slave approach. The conventional whole body master-slave approaches need static balancing assumption or a certain time length of planning after operator's input. Then, we introduce a set of limitations that allows the robot to execute human's daily dynamic bipedal locomotion, but forbid dangerous motions like the COM will be gone outside of the support region. In the limitations, we regulate COM velocity based on a positional relation of the Divergent Component of Motion (Capture Point) and the both feet, and automatically modify the swing foot contact timing with judging the ZMP is inside or outside of the single foot support region. At last, we conducted some experiments of the real time master-slave locomotion with using two life-sized humanoid robots and confirmed the effectiveness of our novel limitation methods.

To enable robotic sensing for tasks with requirements on weight, size, and cost, we develop an ultra-tiny line laser range sensor based on the Time-of-Flight (TOF) principle. With delicate circuit design and optical attachments, we create a sensor as small as 35[mm] × 27[mm] × 30[mm] and as light as 20[g]. The line sensor samples 272 pixels (256 effective pixels) uniformly distributed within the measurement field of view customizable using different laser lenses. The optimal measurement range of the sensor is 0.05[m] ~ 2[m]. Higher sampling rates can be achieved with a shorter range. The sensor can also extend its range to 3[m] with reduced accuracy. We model the overall errors of the sensor and formulate calibration methods, achieving repeatable accuracy and measurement bias both within 2[cm] with our tested ambient lighting conditions and measurement ranges. The sensor is applicable to range sensing tasks including humanoid hand-eye measurement, UAV safe landing, tiny robot range sensing, and object detection.

In this paper, we develop a waterproof suit for humanoid robots and propose an underwater walking control method. Although very few life-sized humanoid robots are completely waterproof, we can easily make these humanoid robots watertight by putting a waterproof suit on them. In water, humanoid robots are influenced by the two forces due to the water: buoyancy and drag force. We take buoyancy into account when generating a walking pattern because the force is large and easy to estimate before walking. However, drag force is small and difficult to precisely predict and therefore, we treat the force as an unknown disturbance. In our method, we modify footsteps based on the Capture Point in order to deal with large disturbances. We verify the effectiveness of the proposed methods through an experiment in which a life-sized humanoid robot walks on a floor, stairs and debris in water.

To achieve tasks in unknown environments with high reliability, highly accurate localization during task execution is necessary for humanoid robots. In this paper, we discuss a localization system which can be applied to a humanoid robot when executing tasks in the real world. During such tasks, humanoid robots typically do not possess a referential to a constant horizontal plane which can in turn be used as part of fast and cost efficient localization methods. We solve this problem by first computing an improved odometry estimate through fusing visual odometry, feedforward commands from gait generator and orientation from inertia sensors. This estimate is used to generate a 3D point cloud from the accumulation of successive laser scans and such point cloud is then properly sliced to create a constant height horizontal virtual scan. Finally, this slice is used as an observation base and fed to a 2D SLAM method. The fusion process uses a velocity error model to achieve greater accuracy, which parameters are measured on the real robot. We evaluate our localization system in a real world task execution experiment using the JAXON robot and show how our system can be used as a practical solution for humanoid robots localization during complex tasks execution processes.

In this paper we propose a new method to detumble a malfunctioning satellite. Large space debris such as malfunctioning satellites generally rotates with nutational motion. Thus several researches have proposed the methods to use a space robot for capturing and deorbiting these debris. The most of the past studies considered the method to detumble an uncontrollable satellite and then capture a single spinning satellite. However these methods require physical contact with malfunctioning satellites, which has a risk of accident. Therefore, we propose a method with an eddy current brake. The eddy current brake system can produce braking force to the target without any physical contact. Thus, we can reduce the risk of critical collision between the space robot and the target object. This paper firstly reviews dynamics of a tumbling satellite and proposes a detumbling strategy with the eddy current brake. We carry out a fundamental experiment to evaluate the performance of the braking force of the developed eddy current brake system, and then we simulate detumbling operation by using the experimental data and show an effectiveness of the proposed detumbling method.