Papers - Murakami, Toshiyuki

Underactuated Control for Two-Wheeled Mobile Robot with an Arm Using Torque Constraint Conditions and Disturbance Observer

Ito J., Murakami T.

IEEE International Symposium on Industrial Electronics (IEEE International Symposium on Industrial Electronics)  2023-June 2023

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This paper presents an underactuated control system for a two-wheeled mobile robot (TWMR). TWMR is expected to use as an autonomous mobile robot (AMR) that works in human-collaborative spaces. TWMR has a smaller footprint and higher center of gravity (CoG), than typical AMRs. Furthermore, in this study, TWMR has an arm. Therefore, TWMR is superior in handling loads in human-presence spaces. However, TWMR is the underactuated system in the body's translational position and tilting angle. In addition, TWMR is affected by disturbances caused by loads. As a robust underactuated control system, the cascade PI/PD and synthesized pitch angle disturbance observer (SPADO) are considered. The cascade PI/PD results in significant translational position error and oscillatory responses. To cope with this problem, a proposed method minimizes both errors of the translational position and tilting angle within torque constraints. The proposed method utilizes the predictive functional control (PFC) for the underactuated control considering constraints. SPADO improves the accuracy of an internal model of PFC. The validity of the proposed method was confirmed compared with the cascade PI/PD through the simulation.

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A Method of Predicting Posture-related Pain Using Biomechanical Parameters for Patients with Lumbar Spinal Disc Herniation

Hatsushiro A., Tawaki Y., Murakami T.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS)   2023

ISSN  1557170X

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Lumbar spinal disc herniation is a disease in which the protruding nucleus pulposus presses on the nerve due to actions that place loads on the disc, causing pain in the lower back and lower limbs. About 80% of treatments of disc herniation are conservative treatments, and although it is necessary to live with pain for a long time, there have been no studies that clearly define the relationship between pain and biomechanical parameters. In this study, we proposed a method of identifying biomechanical parameters that predict posture-related pain in patients with lumbar spinal disc herniation. The pain values were quantitatively evaluated by the Numerical Rating Scale (NRS) and the biomechanical parameters were analyzed by OpenSim. Lasso regression was performed to narrow down the biomechanical parameters that were related to pain and derive the mathematical model of the relationship. Therefore, many of the parameters of the obtained mathematical model were related to the lumbar spine and were consistent with areas that be related to lumbar spinal disc herniation.

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Identification of unknown object properties based on tactile motion sequence using 2-finger gripper robot

Thompson J., Kasun Prasanga D., Murakami T.

Precision Engineering (Precision Engineering)  74   347 - 357 2022.03

ISSN  01416359

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The purpose of service robots is to work and handle a wide range of objects in a human environment. Therefore, they must have the ability to grasp unknown objects with the appropriate force, by dynamically identifying their stiffness, mass, and surface-interaction properties. To ensure the successful grasping of unknown objects, it is significant to estimate the object response properties. In this paper, the cognitive functions to efficiently perform such operations with only tactile motion data and supervised learning using limited data, have been demonstrated. The study uses pinch-grasping performed by a 2-fingered robot experimental setup with a pre-designed motion sequence, over 7 different objects having a wide range of properties to capture the motion data. The proposed approach avails pre-processed motion data to train neural networks for accurately predicting object response properties for 3 unseen test objects. We have done a comparative study among three neural network architectures CNN, LSTM, and CNN-LSTM and we found that novel CNN-LSTM outperforms the other two models in terms of accuracy. The CNN-LSTM regression model achieves 0.98 and 0.97 of R2 value for the prediction of stiffness and mass, respectively and the CNN classification model achieves 94% of accuracy for the surface interaction classification.

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Cognitive Grasping and Manipulation of Unknown Object with Control Grip Force using Cyber Physical System Approach

Thompson J., Murakami T.

IEEJ Journal of Industry Applications (IEEJ Journal of Industry Applications)  11 ( 6 ) 744 - 751 2022

ISSN  21871094

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Service robots working in human environments must have the ability to grasp a wide variety of unseen objects with appropriate grip force without knowing their properties and its response to action in a human environment. This research uses a novel Cyber Physical System framework to estimate and apply minimum grasping force for unknown objects under a task motion using only tactile motion data captured from sensor-less acceleration-based controlled common gripper. The goal is to use this novel framework for developing functions for position-controlled robots to perform real-time cognitive grasping and enable quick implementation across multiple robots. This paper uses soft sensing inputs from the earlier research to characterize unknown object properties like stiffness, mass and surface interaction and show how a data-based analytics algorithm learns a wide range of object properties and slip status along with task action dynamics features, to propose the grasping action with minimum applied force. We validated that the minimum grasping force is able to hold the object firmly during any task motion. In order to improve the learning, the paper proposes a part of the framework to use virtual simulation to gather more learning data and show results that compare well between simulated results with experimental data. We use the simulated data to train Reinforcement Learning approach and show that small variation in object width can be learnt to identify optimum gripping position.

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Comparison of Filtering Methods in Measuring Human ZMP Using Kinect Sensor

Nagasawa T., Tawaki Y., Murakami T.

IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2022-October 2022

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This paper aims to verify the detection accuracy of Zero Moment Point (ZMP) measurements of the human body using the Kinect sensor. In this paper, ZMP is measured based on a multi-link model of the human body. ZMP calculation algorithms using a Low Pass Filter (LPF) and Savitzky-Golay (SG) filter were constructed to investigate filtering methods that can measure ZMP with high accuracy and small lag. The accuracy and responsiveness of these filters were evaluated through experiments measuring ZMP during human walking. Experimental results show that the detection error in ZMP is dominated by the differential noise in the acceleration calculation, and applying the filter only to measured acceleration values increases responsiveness with the same accuracy as when applied to ZMP. We also found that the SG filter is superior to LPF in noise suppression and responsiveness of ZMP measurements, though it occurs overshoot in measurements.

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Evaluation of Mathematical Models for Postural Sway Based on Reproducibility of SDA Parameters

Sakae K., Tawaki Y., Murakami T.

IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2022-October 2022

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Evaluation of the falling risk is significant for older people not to fall and become in need of care. The static posturography test is adopted to evaluate the lack of balance ability that causes the falling. This test measures the center of pressure (COP) of humans and evaluates it by analyzing the data. There are three main analysis methods: descriptive statistics, stabilogram diffusion analysis (SDA), and mathematical modeling. Descriptive statistics and SDA represent only statistical values without the mechanism of the posture control system. However, mathematical modeling evaluates the system from the model coefficients containing physical meanings, and we focus on it. The stochastic differential equation of stiffness, viscosity, and stochastic terms are introduced to the mathematical model for the static posturography test. The COP trajectory reproducibility of the model is evaluated using SDA. SDA is a time-based analysis suitable for evaluating the dynamic posture control system. In the experiment, we compare the SDA parameters between older and younger subjects and evaluate the reproducibility of the model using the SDA parameters. As a result, we confirm that the SDA parameters can classify based on age to a certain extent, and the model has higher reproducibility than the conventional model against SDA.

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Position and Cross-Coupling Factors Estimation for Sliding Mode Current Control based Position-Sensorless Control of IPMSM

Shimamoto K., Murakami T.

IEEE Access (IEEE Access)   2022

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This paper presents a control method with an estimation method of cross-coupling factors of Interior Permanent Magnet Synchronous Motors (IPMSM) inductance for position-sensorless servo drive systems. The cross-coupling factors are from dq-axis mutual inductance. Conventionally, the cross-coupling factors have been ignored in the IPMSM model and deteriorate control performance. That has caused decreasing robustness and velocity vibration in the low-speed range. Since the cross-coupling factors vary with the rotor position and the current, it is hard to measure them. Therefore, the proposed method utilizes a high-frequency voltage injection method to estimate the cross-coupling factors online. In addition, the proposed current control method utilizes a sliding mode control and voltage disturbance observer based on the voltage equation, including the dq-axis mutual inductance model. The estimated cross-coupling factors are reflected in the proposed current controller instantaneously. Experimental results show that the proposed method considering cross-coupling factors increases the robustness to the disturbance force and reduces the velocity vibration.

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Performance Evaluation of Force Control and Reaction Force Estimation in Force Sensorless Hybrid Control for Workspace Based Controller

Shimamoto Keita, Murakami Toshiyuki

2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    231 - 236 2022

ISSN  1943-6572

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Velocity and Attitude Control of Quadcopter with Suspended-payload using Disturbance Observer with Payload Inclination Suppression

Sugaya Taketo, Murakami Toshiyuki

2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    414 - 419 2022

ISSN  1943-6572

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Position Control Considering Slip Motion of Tracked Vehicle Using Driving Force Distribution and Lateral Disturbance Suppression

Kuwahara H., Murakami T.

IEEE Access (IEEE Access)  10   20571 - 20580 2022

ISSN  2169-3536

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Complex slippage and nonholonomic constraints can disturb the precise movement of tracked vehicles. In this study, a position control system using driving force control and virtual-turning velocity control (VTVC) was established for a tracked vehicle. Slippage in the translational direction can be suppressed by controlling the driving force of the crawlers, estimated using the vehicle velocity. However, the driving forces interfere with each other in a turning motion. Therefore, a driving force distribution method was developed using the instantaneous turning center of a vehicle to decouple the forces. This distribution induced slippage in the direction of turning. In addition, a virtual reference was derived from the vehicle velocity and lateral disturbance, which described the effects of the nonholonomic constraints and skidding of the tracked vehicle. Next, a VTVC method was developed to suppress the lateral disturbance by controlling the turning velocity to follow the virtual reference. The experimental results confirm that the proposed approach ensures high-performance position tracking and adequate slippage of the tracked vehicle.

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Estimation of Jacobian Matrix without accelerometer on Omni-directional Mobile Walker

Ominato Kentaro, Murakami Toshiyuki

2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    329 - 334 2022

ISSN  1943-6572

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Frequency Characteristics of Power Transformer for Isolated DC-DC Converter

Nakamura T., Murakami T.

IEEE Access (IEEE Access)  10   11633 - 11641 2022

ISSN  2169-3536

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The operational frequency of a transformer is an important factor in the configuration of an isolated DC-DC converter. However, discussions of this frequency are inadequate. This study focuses on the frequency characteristics of the transformers. The frequency characteristics of the impedance and loss of the transformer were obtained to explain their fundamental attributes. When a transformer is employed in a power electronic transformer (PET), the waveform of the voltage is rectangular. The loss under this waveform was obtained in order to observe its characteristics. Furthermore, the problems with the isolated DC-DC converter are explained. The natural frequency, composed of leakage inductance and equivalent-parallel capacitance, determines the performance of the isolated DC-DC converter. When the operational frequency of the isolated DC-DC converter is below its natural frequency, the loss increases under the no-load or light-load conditions. This increase in the loss is caused by the current, which contains the natural frequency of the transformer owing to the ringing.

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Model-Free Detection of Penetration and Automatic Stop Control in Dental Implant Surgery Based on Differential Value of Torque

Kido Yusuke, Kawana Hiromasa, Asoda Seiji, Nozaki Takahiro, Murakami Toshiyuki

2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    144 - 149 2022

ISSN  1943-6572

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Object Detection in Motion Reproduction System with Segmentation Algorithm

Sun Xiaobai, Nozaki Takahiro, Ohnishi Kouhei, Murakami Toshiyuki

2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    42 - 47 2022

ISSN  1943-6572

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Classification of Older and Fall-Experienced Subjects by Postural Sway Data using Mass Spring Damper Model.

Yuta Tawaki, Takuichi Nishimura, Toshiyuki Murakami

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (IEEE Transactions on Neural Systems and Rehabilitation Engineering)  30   40 - 49 2022

ISSN  15344320

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The quiet standing test is used to detect diseases of the postural control system. The descriptive statistics of the center of pressure (COP) of older people during the test tend to be larger than those of healthy young people, but they cannot indicate structural problems in postural control. COP trajectories can be mathematically modeled with structural parameters such as viscosity, stiffness, and stochastic terms; however, the classification accuracy of older and fall-experienced people using such parameters has not been sufficiently verified. In this study, six structural parameters of a mass-spring-damper (MSD) model were estimated using two datasets, in which a total of 212 subjects performed quiet standing tests under four conditions. The estimated parameters were used for classification with a random forest algorithm to examine the differences in classification accuracy compared to seven conventional descriptive statistics methods. For the classification of older subjects, the classification accuracy of the MSD parameter method was the highest in foam condition, with positive likelihood ratios approximately 8.0. For the classification of fall-experienced subjects, the positive likelihood ratio of the MSD parameter method was 5.0, which is better than conventional descriptive statistics. Various MSD parameters revealed that aging and changing the floor surface and visual conditions cause oscillations in the COP behavior. While the MSD parameters were confirmed to help classify older subjects more accurately than the conventional descriptive statistics, there was room for further improvement in the classification accuracy of fall-experienced subjects.

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An Approach of Load-Side Disturbance Rejection Control for Series Elastic Actuators

Hiraoka Atsushi, Murakami Toshiyuki

2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC)    18 - 23 2022

ISSN  1943-6572

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Realization of Synchronized Movement between Caregiver and Electric Wheelchair

Hirata K., Murakami T., Sasayama M.

IEEE International Symposium on Industrial Electronics (IEEE International Symposium on Industrial Electronics)  2021-June 2021.06

ISSN  2163-5137

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A caregiver has an important role to not only help patients with high levels of disability to move around, but also be aware and manage the patient's state of health. Visual cues on the patient's expression is an especially important source of information on the patient's well-being, especially for those with high levels limitations on cue sending, such as Amyotrophic Lateral Sclerosis (ALS) patients. Thus, this paper proposes a system that enables the caregiver to control the movement of the wheelchair while waking alongside the wheelchair where they can also interact with the patient directly. The proposed approach has been validated through experiments.

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Trajectory Tracking Control with Estimated Driving Force for Tracked Vehicle Using Disturbance Observer and Machine Learning

Kuwahara H., Murakami T.

IEEE International Symposium on Industrial Electronics (IEEE International Symposium on Industrial Electronics)  2021-June 2021.06

ISSN  2163-5137

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This paper proposes a tracking control method that suppresses slippage by using the driving force of a tracked vehicle. First, the velocity of the tracked vehicle including slippage is estimated using a disturbance observer and machine learning technique. This estimated velocity is utilized to design an observer that can estimate the driving force of the crawler. By distributing and controlling the driving force, tracking control with reduced slippage can be realized. The experimental results demonstrate the tracking performance of the proposed control system.

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Assessment of human walking stability using the gait sensitivity norm with wearable sensors

Masuda H., Fukutoku K., Murakami T.

2021 IEEE International Conference on Mechatronics, ICM 2021 (2021 IEEE International Conference on Mechatronics, ICM 2021)   2021.03

ISSN  9781728144429

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Quantifying walking stability is needed in order to evaluate the various walking assist methods. It can also allow the planning of individualized interventions for elderly people or patients with disorders. The Gait Sensitivity Norm (GSN) is a new measure of the walking stability developed for passive dynamic walkers and has been reported to show a strong correlation with the fall risk. The GSN is a method based on the idea of the H2 norm, which allows us to know the dynamic response of the system of walkers by measuring the impulse response. The reliability of the GSN quantification has been confirmed in passive dynamic walkers and neuromusculoskeletal walking models. However, it has not yet been applied to humans. In this paper, we proposed a method to apply the GSN to the analysis of human walking. To apply the GSN to a human gait, wearable sensors were used to analyze human walking. The validity of quantifying gait stability with the GSN is assessed in the experiments comparing abnormal walker (with some weight or blindfold) and normal walkers. The result is consistent with the intuitive idea that blind walking is more unstable than normal walking.

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Admittance control-based bilateral control system considering position error

Kimura S., Nozaki T., Murakami T.

2021 IEEE International Conference on Mechatronics, ICM 2021 (2021 IEEE International Conference on Mechatronics, ICM 2021)   2021.03

ISSN  9781728144429

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This paper proposes a bilateral control system implementing an admittance control system. Bilateral control system realizes teleoperation of a remote robot with a sense of touch. We focus on an admittance-based bilateral control system, which needs only two communication channels and has almost the same control performance as an acceleration-based bilateral control system, which is one of the highest transparent teleoperation systems. However, the conventional admittance-based system assumes an ideal communication situation where there is no communication time delay and no packet loss and has possible to increase position error as time goes on in practical use. The proposed admittance-based system achieves the same control performance as the conventional structure without increasing position error even if there is a communication delay. The validity of the proposed system is confirmed through simulations and experiments.

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