Published papers

© 2019 by the authors. This paper proposes a nonlinear control method for carrying out Minimum-time satellite attitude maneuver and antenna motion which have robustness against model uncertainty. In recent years, small Earth observation satellites have been utilized and expected to maneuver rapidly in missions such as multi-target acquisition. On the other hand, small satellites need to send the observation data to ground station. Recently, small Earth observation satellites acquire high-resolution data, resulting in an increase in the time required for data communication. Thus, small satellites need to use inter-orbit communication link through Data Relay test satellite sending data from Data Relay communication (DRC) antenna. In conventional operations, the antenna motion is implemented after satellite attitude maneuver. However, this method has a time delay between the completion of the attitude maneuver and the start of data communication. The purpose of this study is to extend the time of earth observation and data communication by carrying out satellite maneuver and antenna motion concurrently. Because small satellite mounted with DRC antenna has large mass ratio of the antenna, we cannot ignore time variability of the moment of inertia of the whole system and reaction torque generated by antenna motion. Hence, in order to take the influence of the antenna motion into consideration, we combine a satellite attitude control system and an antenna drive system into one control system by governing equations and constructing the optimal control problem. We convert the optimal control problem into a NLP by discretizing the control input (a series of pulses) to minimize the final time of the total maneuver that includes the antenna adjustment. In addition, it is considered that a model uncertainty and unknown disturbance occurs in real space. Thus, we have to design feedback controller to secure robustness in model error and unknown disturbance. Accordingly in order to propose a nonlinear control method for carrying out minimum-time satellite attitude maneuver and antenna motion which have robustness against model uncertainty and unknown disturbance, we calculate a reference attitude by application of optimal control input torque to ideal satellite model and design servo controller by using state-dependent Riccati equation (SDRE) control method in order to track time-variant reference attitude.

© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. This paper proposes a simultaneous control method for small satellites mounted with a communication antenna; the objective is to reduce the time involved in satellite maneuver and antenna motion. Recently, small Earth observation satellites have been utilized, even though agile large angle satellite attitude maneuver has been in demand. Small Earth observation satellites acquire high-resolution data, resulting in an increase in the time required for data communication. Therefore, it has become important to ensure that small Earth observation satellites are capable of being maneuvered rapidly so that communication time can be extended by using a data relay system. In conventional operations, the antenna motion is implemented after satellite attitude maneuver. However, this method has a time delay between the completion of the attitude maneuver and the start of data communication. The purpose of this study is to extend the time for Earth observation and data communication. In order to achieve this, we propose a simultaneous control method for satellite maneuver and antenna motion using a nonlinear programming problem.

© 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. In recent years, bird strikes are increasing with the increase in the number of airliner flights. Therefore, measures against bird strikes are required. Collisions between an aircraft and a flock of birds during takeoff and landing are numerous and can cause serious damage. Related works have been conducted to prevent entry of a flock of birds into the runway. The purpose of this study was to guide a flock of birds into avoiding the runway using an autonomous drone. Guidance was successful in simulations and experiments, provided that the drone was located near a flock of birds. Therefore, in this study, assuming that the drones are placed around the runway and far from the flock, we propose a control method to move the drone towards the flock and guide the birds to prevent bird strikes. In order to realize interception and guidance under such conditions, we predict the trajectories of the bird flock using a model of birds. Setting the target position of the drone on the predicted trajectories allows the drone to intercept the birds without unnecessary movement of the drone. Because the drone is in the same speed range as the birds, we determine the drone’s control input so as to satisfy the velocity constraint using model predictive control (MPC). In this study, we propose a control method for autonomous drones that considers the model of birds, aimed at guiding a flock of birds to prevent bird strike. We verify the performance of the proposed method by conducting numerical analysis based on a model of a realistic runway.

© 2017 IEEE. This paper describes the motion control system for a powered wheelchair using eye gaze in an unknown environment. Recently, new Human-Computer Interfaces (HCIs) that have replaced joysticks have been developed for a person with a disability of the upper body. In this paper, movement of the eyes is used as an HCI. The wheelchair control system proposed in this study aims to achieve an operation such that a passenger gazes towards the direction he or she wants to move in the unknown environment. This paper presents a system based on gaze detection and environment recognition that are integrated by the fuzzy set theory in real time. This motion control system can support safe and smooth movement of the wheelchair by automatically calculating its direction of motion and velocity, to avoid obstacles and move in the gaze direction of the passenger. The effectiveness of the proposed system is demonstrated through experiments in a real environment.

© 2019, Springer Nature Switzerland AG. In a human–robot interaction, a robot must move to a position where the robot can obtain precise information of people, such as positions, postures, and voice. This is because the accuracy of human recognition depends on the positional relation between the person and robot. In addition, the robot should choose what sensor data needs to be focused on during the task that involves the interaction. Therefore, we should change a path approaching the people to improve human recognition accuracy for ease of performing the task. Accordingly, we need to design a path-planning method considering sensor characteristics, human recognition accuracy, and the task contents simultaneously. Although some previous studies proposed path-planning methods considering sensor characteristics, they did not consider the task and the human recognition accuracy, which was important for practical application. Consequently, we present a path-planning method considering the multimodal information which fusion the task contents and the human recognition accuracy simultaneously.

© 2019, Springer Nature Switzerland AG. Two-wheeled service robots capable of following a person are an active research topic. These robots will support and follow customers like tourists to many places. It is necessary that an appropriate distance be maintained between the human and the robot. In addition, robots need to not only approach but also turn toward the human to provide services when the human stops walking. Therefore, the control system should change its property depending on the situation. However, many of the previous researches report an algorithm having only one property. Thus, this research proposed a motion control system of a two-wheeled service robot that could turn around while simultaneously following a human. To achieve this, we use nonlinear model predictive control (NMPC) and evaluation function weights depending on the relative distance between robots and human.

© 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. Earth observation satellites repeatedly charge and discharge their batteries in harsh environments, where sunlight illumination and shade occur repetitively; thus, battery power deteriorates rapidly. In this study, variable speed control moment gyro (VSCMG) / integrated power and attitude control system (IPACS), which has both an attitude control function and an energy storage function, was used for a lithium-ion battery and a hybrid. We propose a control law that suppresses the chemical deterioration factor of the battery while achieving attitude control by cooperatively charging and discharging the required power. The proposed method calculates the commands of VSCMG/IPACS and the power distribution ratio of the battery and VSCMG/IPACS at the same time, for power distribution that accounts for the reference torque. The proposed method considers the torque error, the wheel angular velocity variation, and the wheel angular acceleration variation, to ensure attitude control performance. In addition, to suppress the deterioration factor of the battery, an evaluation function considering the SOC and C rate of the battery is designed. While constraints on the output power, motor, and battery are satisfied, we obtain the optimal solution that minimizes the evaluation function. Using the above algorithm, the proposed method can yield optimal power distribution and commands of VSCMG/IPACS.

Falling is a serious problem with the growing elderly population. In this sense, clinical institutions have implemented motor function assessment programs. In particular, the timed up and go test (TUG) is the most frequently applied clinical trial to assess the elderly walking ability in many clinical institutions and communities. In this study, we proposed a gait measurement system that can evaluate motor function in dynamic gait tests, such as the TUG test, using the point clouds of depth sensors (Kinect). The TUG test is a dynamic task that includes 3m of walking and turning motion. However, estimating joint positions using conventional methods that use Kinect skeleton function or point clouds is difficult. To solve these problems, before applying the iterative closest point algorithm, we proposed a method to move the segment model to a pre-estimated position and perform matching. In the accuracy verification experiments of several young people, the average error of each joint position was less than approximately 0.03 m, and the average error of the knee angle was approximately 4.54 to 5.13 degrees. These results indicate that the values estimated by the proposed method are useful as values for evaluating clinical tasks.

Objective: Knee osteoarthritis (OA) has been suggested to increase the risk of falls. Low back pain (LBP) is a potential risk factor for falls in people with knee OA, but this issue has not been addressed adequately in previous studies. The objective of this study was to investigate the relationship between LBP and falls in people with knee OA in a 12-month period. Methods: Participants with knee OA (Kellgren/Lawrence [K/L] grade ≥1) completed questionnaires for LBP and falls that occurred in the preceding 12 months. Binary and ordinal logistic regression analyses were performed to assess the relationship between LBP or moderate-to-severe LBP (numeric rating scale ≥4 points) and any fall (≥1 fall) or recurrent falls (≥2 falls) after adjustment for age, sex, K/L grade, knee pain severity, and quadriceps strength. Sensitivity analyses were performed excluding people with sciatica, nonchronic LBP, K/L grade 1, and those receiving pain medications. Results: We included 189 participants (ages 61–90 years, 78.3% women) in this study. Of these participants, 41 (21.6%) reported falls in the preceding 12 months. People with any LBP (n = 101) and those with moderate-to-severe LBP (n = 45) had 2.7- and 3.7-times higher odds of recurrent falls, respectively. Sensitivity analyses revealed a strong correlation between moderate-to-severe LBP and recurrent falls. Conclusion: Thorough investigation of LBP as a risk factor for recurrent falls in people with knee OA may provide a novel insight into the pathomechanics of recurrent falls in this population.

© 2018 Iijima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective This study aimed to determine whether kilohertz-frequency alternating current (KFAC) is superior to low-frequency pulsed current (PC) in increasing muscle-evoked torque and lessening discomfort. Data sources The electronic databases PubMed, PEDro, CINAHL, and CENTRAL were searched for related articles, published before August 2017. Furthermore, citation search was performed on the original record using Web of Science. Review methods Randomized controlled trials, quasi-experimental studies, and within-subject repeated studies evaluating and comparing KFAC and PC treatments were included. The pooled standardized mean differences (SMDs) of KFAC and PC treatments, with 95% confidence intervals (CIs), were calculated using the random effects model. Results In total, 1148 potentially relevant articles were selected, of which 14 articles with within-subject repeated designs (271 participants, mean age: 26.4 years) met the inclusion criteria. KFAC did not significantly increase muscle-evoked torque, compared to PC (pooled SMD: -0.25; 95% CI: -0.53, 0.06; P = 0.120). KFAC had comparable discomfort compared to that experienced using PC (pooled SMD: -0.06; 95% CI: -0.50, 0.38; P = 0.800). These estimates of the effects had a high risk of bias, as assessed using the Downs and Black scale, and were highly heterogeneous studies. Conclusions This meta-analysis does not establish that KFAC is superior to PC in increasing muscle-evoked torque and lessening discomfort level. However, no strong conclusion could be drawn because of a high risk of bias and a large amount of heterogeneity. High quality studies comparing the efficacy between PC and KFAC treatments with consideration of potential confounders is warranted to facilitate the development of effective treatment.

© 2018 Elsevier B.V. Background: Stair climbing was suggested to be the first affected task in individuals with knee osteoarthritis (OA). Research question: This review aimed to identify consistent kinematic, kinetic, and spatiotemporal alterations of stair climbing exhibited by individuals with knee OA. Methods: A literature search published until September 2017 was conducted in PubMed, PEDro, CINAHL, and Cochrane CENTRAL. Reviewer extracted data in accordance with the Cochrane Handbook. Where possible, data were combined into a meta-analysis; the pooled standardized mean differences between individuals with knee OA and healthy adults were calculated using the random-effect model. Results: In total, 585 potentially relevant articles were selected, of which 12 (695 participants, mean age: 58.4 years) met the inclusion criteria. Meta-analysis revealed that kinematic and kinetic alterations during stair climbing associated with knee OA were lower external knee flexion moment in conjunction with a larger trunk/hip flexion angles and smaller knee flexion/ankle dorsiflexion angles. Individuals with knee OA showed a delayed quadriceps activation during stair ascent. A lack of evidence was detected for alterations in external knee adduction moment during stair climbing. Effect estimate in each meta-analysis was judged “very low” on the GRADE approach. Significance: No strong conclusion can be drawn because of the low quality of evidence; however, individuals with knee OA may exhibit altered kinematics and kinetics changes in sagittal plane during stair climbing, and have delayed quadriceps muscle activity. Further studies with adequate adjustment for confounders are warranted to facilitate clinical hallmarks of the knee OA, particularly in early stages of the disease.

© 2018 by the authors. This paper describes the motion control system for a powered wheelchair using eye gaze in an unknown environment. Recently, new Human-Computer Interfaces (HCIs) that have replaced joysticks have been developed for a person with a disability of the upper body. In this paper, movement of the eyes is used as an HCI. The wheelchair control system proposed in this study aims to achieve an operation such that a passenger gazes towards the direction he or she wants to move in the unknown environment. Implementation of such an operating method facilitates easy and accurate movement of the wheelchair even in complicated environments comprising passages on the same side. This paper presents a system based on gaze detection and environment recognition that are integrated by the fuzzy set theory in real time. In the fuzzy set theory, we achieve the movement to the passage which a passenger gazes towards among some passages by integrating the information of some passages and gaze. Moreover, we design it with consideration of uncertain gaze input by using the value of gaze detection accuracy. Moreover, we achieve obstacle avoidance by integrating the information of obstacles. This motion control system can support safe and smooth movement of the wheelchair by automatically calculating its direction of motion and velocity, to avoid obstacles and move in the gaze direction of the passenger. The effectiveness of the proposed system is demonstrated through experiments in a real environment.

© 2016 by the authors. In recent years there has been an increasing need to improve satellite attitude control performance in terms of agility and attitude accuracy in large-angle attitude maneuvers. To achieve such control performance, single-gimbal control moment gyros (SGCMGs) should be mounted as modern-type actuators. Conventionally, based on the torque command calculated by the attitude control system of the satellite, SGCMGs were controlled by solving inverse kinematics through a pseudo inverse matrix steering law. However, in such a control system structure, it may be difficult to obtain the desired torque required by the attitude control system because of the singularity problem of SGCMGs. Furthermore, with respect to implementation, since the condition number of the Jacobian matrix of SGCMG becomes extremely large in the singularity, the numerical calculation error of the pseudo inverse matrix increases greatly. Therefore, we propose an overall control system that can solve above-described problems and the state-dependent Riccati equation (SDRE) control system that integrates the satellite and SGCMG system. The proposed optimal control system, which does not solve the pseudo inverse matrix, can realize gimbal angle guidance by gimbal angle feedback and singularity avoidance/escape using the biased weighting matrix. In the numerical simulation, the usefulness of proposed system is shown in comparison with the conventional system.

© 2020, Springer Nature B.V. To complete a task consisting of a series of actions that involve human-robot interaction, it is necessary to plan a motion that considers each action individually as well as in relation to the following action. We then focus on the specific action of “approaching a group of people” in order to accurately obtain human data that is used to make the performance of tasks involving interactions with multiple people more smooth. The movement depends on the characteristics of the important sensors used for the task and on the placement of people at and around the destination. Considering the multiple tasks and placement of people, the pre-calculation of the destinations and paths is difficult. This paper thus presents a system of navigation that can accurately obtain human data based on sensor characteristics, task content, and real-time sensor data for processes involving human-robot interaction (HRI); this method does not navigate specifically toward a previously determined static point. Our goal was achieved by using a multimodal path planning based on integration of action modeling by considering both voice and image sensing of interacting people as well as obstacle avoidance. We experimentally verified our method by using a robot in a coffee shop environment.

© 2018 IEEE. This paper presents a novel calibration method of insole sensors to estimate vertical ground reaction force (vGRF) during walking using the Wii Balance Board (WBB) as an accessible alternative to costly force plates. The sensor forces were weighted using linear least-squares regression to fit to the measurements of the WBB during walking and standing. By comparison with force plates, the accuracies of the vGRF estimated by the method with walking through the WBB were equivalent to the force plate-based calibration. In addition, the method using standing on the WBB did not have large deteriorations when compared to the above methods.

© 2017 IEEE. Ground reaction force (GRF) estimations using instrumented insoles relied on the use of costly force plates in previous works. This paper designed insoles with 15 force sensing resisters and presents an accessible estimation method of vertical GRF (vGRF) using the insole without any cost-prohibitive devices. To determine vGRF from the insole sensor forces, a subject-specific linear regression model was constructed using a least-squares method with a constraint and a bound. The regression matched the sensor forces during single-leg standing (SLS) to a subject's body weight with a linear constraint using data measured while walking. During SLS, standing static and shifting body weight were performed to enhance estimation accuracies. The accuracies of constructed models while walking were evaluated by comparison with the Nintendo Wii Balance Board (WBB) which can measure accurate vGRF compared with force plates. The results for an adult had 8-15 % root mean squared errors (RMSEs) with no significant deviations from previous methods which relied on force plates. From these results, the proposed method was validated as an accessible kinetic gait analysis system.

© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. In this research, we propose a design method for a nonlinear optimal attitude control system that combines the systems of a single-gimbal control moment gyro (SGCMG) and a satellite that were conventionally designed separately. For this purpose, we designed a state-dependent linear representation model integrating satellite dynamics and SGCMG dynamics using a State-Dependent Riccati Equation (SDRE) controller. In the proposed method, it is possible to design the gimbal angular velocity as input without solving the inverse kinematics in the pyramid-type SGCMG. Therefore, it is possible to avoid the singularity of SGCMG by designing the weighting function matrices considering the relationship between the maneuvering axis and SGCMG steering. A numerical simulation shows that it is possible to achieve a high-speed attitude maneuver of the satellite by optimal attitude control considering singularity avoidance by the proposed method. In addition, usefulness of proposed law is shown in comparison with the GSR Inverse steering logic for the agile attitude maneuver.

© 2020 by the authors. Specific physiological changes during pregnancy exert excessive strain on muscles such as the erector spinae (ES) and contribute to low back pain (LBP). The link between LBP and sit-to-stand (STS) motion has previously been investigated through motion analysis using an inertial measurement unit (IMU); however, the factors leading to LBP have not been revealed. Moreover, clinicians require an effective assessment method for reducing the physical burden on pregnant women. Therefore, the investigation of the relationships between motion, muscle load calculated from musculoskeletal model for pregnancy, and the severity of LBP during STS in pregnant women was conducted. Furthermore, this study proposes a method for assessing motion and muscle load during STS using an IMU. The relationship among (i) motion evaluation indices and ES muscle torque, and (ii) the ES torque and the intensity of LBP during STS was investigated. As the results, significant positive correlations were observed between (i) the angular velocity of the torso in the sagittal plane and ES torque, and (ii) two types of evaluation indices of ES torque and intensity of LBP. The proposed method by an IMU attached to the torso could effectively assess ES load related to LBP during STS in pregnant women.

© 2017 IEEE. In the conventional agile attitude maneuver of a satellite, a control system of the satellite and Single Gimbal Control Moment Gyro (SGCMG) is designed separately and stability is not guaranteed under the singularity of SGCMGs. Therefore, in this research, we integrate the satellite and SGCMGs and design a model with the gimbal angular velocity as input. Since the target gimbal angle can be explicitly designed by a null motion, proposed control system is possible to guide the initial gimbal angle which is advantageous for next mission. In addition, it is shown that proposed method can guarantee stability even under the singularity of SGCMGs by the State-Dependent Riccati Equation (SDRE). Moreover, numerical simulations show that the singularity avoidance performance up to the target gimbal angle and the guidance performance of the gimbal angle are higher than the conventional method due to the optimality of gimbal angular velocity input.

© 2018 IEEE. In a human-robot interaction, a robot needs to move to a position where the robot can obtain high reliability data of people, such as positions, postures, and voice. This is because the human recognition reliability depends on the positional relation between the people and the robot. In addition, the robot should choose the sensor data which is necessary to perform the interaction task. Therefore, it is necessary to navigate the robot to the position to obtain the data for initiation of the interaction task. Accordingly, we need to design a path-planning method considering sensor characteristics, human recognition reliability, and task contents. Although previous studies proposed path-planning methods using an interaction potential considering sensor characteristics, they did not consider the task contents and the human recognition reliability, which are important for practical application and did not applied to interaction with multiple people. Consequently, we present a path-planning method considering the task contents and the human recognition reliability using multimodal potential field integrating these information. We verified effectiveness of the path-planning method for interaction with multiple people.