Kyoosik Shin

Development of dynamic model-based controller for upper limb exoskeleton robot

In this paper, we propose and experimentally test a dynamic model-based force controller for the motion of upper limb exoskeleton robot. The system is composed of 3 degrees of freedom using an electrical actuator. This system is mainly controlled by the multi-axis force sensor signals. These are used to generate desired torques for driving the robot system. However, singularities exist when force signals in the Cartesian coordinate system are transformed to torques in the joint coordinate system. So we applied the damped least squares method. In handling loads, torque compensation regarding the weight of the object is required. Therefore, we installed the multi-axis force sensor at the robot end effector. It measures the interaction forces between the exoskeleton and the load. To compensate for the handling object, we used the static model. We performed control stability and load handling experiments to verify the effectiveness of the controller. With these experiments, we confirmed the effectiveness of the proposed controller.

Magnetic fish-robot based on multi-motion control of a flexible magnetic actuator.

This paper presents a biologically inspired fish-robot driven by a single flexible magnetic actuator with a rotating magnetic field in a three-axis Helmholtz coil. Generally, magnetic fish-robots are powered by alternating and gradient magnetic fields, which provide a single motion such as bending the fish-robots fins. On the other hand, a flexible magnetic actuator driven by an external rotating magnetic field can create several gaits such as the bending vibration, the twisting vibration, and their combination. Most magnetic fish-like micro-robots do not have pectoral fins on the side and are simply propelled by the tail fin. The proposed robot can swim and perform a variety of maneuvers with the addition of pectoral fins and control of the magnetic torque direction. In this paper, we find that the robots dynamic actuation correlates with the magnetic actuator and the rotating magnetic field. The proposed robot is also equipped with new features, such as a total of six degrees of freedom, a new control method that stabilizes posture, three-dimensional swimming, a new velocity control, and new turning abilities.

Development of a novel two-limbed parallel mechanism having Schönflies motion

This paper introduces a novel parallel mechanism having Schönflies motion. The mechanism consists of only two RRPaR-type limbs. After a short description of its structure, its position analysis is conducted and its screw-based kinematic model is derived. Next, its singularity analysis is performed via Grassmann line geometry and then its optimal kinematic characteristics are examined with respect to workspace size and isotropy property. The results show that the proposed parallel mechanism has a very high potential to be used as a manipulator or a haptic device. A prototype of this mechanism was developed and tested to corroborate its performance.

Adaptive fuzzy quasi-continuous high-order sliding mode controller for output feedback tracking control of robot manipulators

This article develops a new output feedback tracking control scheme for uncertain robot manipulators with only position measurements. Unlike the conventional sliding mode controller, a quasi-continuous second-order sliding mode controller (QC2C) is first designed. Although the QC2C produces continuous control and less chattering than conventional sliding mode and other high-order sliding mode controllers, chattering exists when the sliding manifold is defined by the equation s = s · = 0 . To alleviate the chattering, an adaptive fuzzy QC2C (FQC2C) is designed, in which the fuzzy system is used to adaptively tune the sliding mode controller gain. Furthermore, in order to eliminate chattering and achieve higher tracking accuracy, quasi-continuous third-order sliding mode controller (QC3C) and fuzzy QC3C (FQC3C) are investigated. These controllers incorporate a super-twisting second-order sliding mode observer for estimating the joint velocities, and a robust exact differentiator to estimate the sliding manifold derivative; therefore, the velocity measurement is not required. Finally, computer simulation results for a PUMA560 industrial robot are also shown to verify the effectiveness of the proposed strategy.

Adaptive impedance control for upper limb assist exoskeleton

Need to develop human bodys posture supervised robots, gave the push to researchers to think over dexterous design of exoskeleton robots. It requires to develop quantitative techniques to assess motor function and generate the command for the robots to act accordingly with complex human structure. In this paper, we present a new technique for the upper limb power exoskeleton robot in which load is gripped by the human subject and not by the robot while the robot assists. Main challenge is to find non-biological signal based human desired motion intention to assist as needed. For this purpose, we used newly developed Muscle Circumference Sensor (MCS) instead of electromyogram (EMG) sensors. MCS together with the force sensors is used to estimate the human interactive force from which desired human motion is extracted using adaptive Radial Basis Function Neural Network (RBFNN). Developed Upper limb power exoskeleton has seven degrees of freedom (DOF) in which five DOF are passive while two are active. Active joints include shoulder and elbow in Sagittal plane while abduction and adduction motion in shoulder joint is provided by the passive joints. To ensure high quality performance model reference based adaptive impedance controller is employed. Exoskeleton performance is evaluated experimentally by a neurologically intact subject which validates the effectiveness.

Backstepping quasi-continuous high-order sliding mode control for a Takagi–Sugeno fuzzy system with an application for a two-link robot control

A new control scheme is proposed for motion tracking of a Takagi–Sugeno fuzzy system using the backstepping quasi-continuous high-order sliding mode (HOSM) control technique. First, a Takagi–Sugeno fuzzy model is used to represent the original second-order nonlinear system; most of the parameters for this model can be computed offline. Next, a conventional backstepping sliding mode control (BSMC) is designed to stabilize and guarantee the exact motion tracking for the Takagi–Sugeno fuzzy system. However, use of the conventional sliding mode control generates significant chattering. Therefore, a quasi-continuous second-order sliding mode (QC2S) control is employed to reduce chattering and obtain higher tracking precision, resulting in a backstepping quasi-continuous second-order sliding mode (BQC2S) control law. Combining the Takagi–Sugeno fuzzy model with the BQC2S controller results in a controller scheme that preserves the advantages of both techniques, such as the low online computational burden of the Takagi–Sugeno fuzzy model, and the low chattering, robustness, and fast transient response of the BQC2S controller. Finally, the proposed controller is used to control a two-link robot manipulator and is compared with the existing approaches. Simulation results are presented to demonstrate the effectiveness of the proposed methodology.

A Pushing Force Mechanism of Magnetic Spiral-type Machine for Wireless Medical-Robots in Therapy and Diagnosis

In this paper, we present a pushing force mechanism in a magnetic spiral-type machine for use in therapy and diagnosis. Non of the current spiral-type machines can create a pushing force. Thus, their locomotion or tasks are controlled by magnetic field strength and driving frequency. However, the proposed mechanism increases the thrust force on the robot itself in the working space without field controls. The developed pushing force mechanism uses a magnetic suspension structure based on two magnets between the two spiraltype machines. Through this mechanism, the two spiral-type machines act independently via a rotating magnetic field. Thus, the different thrust forces between the two machines create a variation of the magnetic repulsive force in the magnetic suspension. Therefore, the combination of the two thrust forces and the magnetic repulsive force become a total propulsive force. The prototype of the mechanism increased the total thrust force by approximately 3.6 times for locomotion and generated a maximum pushing force of 0.345 N.

Analysis of a Novel Transverse Flux Type Permanent Magnet Reluctance Generator

This paper proposes a novel transverse flux type permanent magnet reluctance generator (TFPMRG), which contains a permanent magnet (PM) in its U-shaped salient stator pole. A U-shaped stator core is designed with the short flux path to reduce the mutual effect between phases. Moreover, the proposed TFPMRG shape is designed for using PM instead of an excitation circuit to provide the field excitation, which increases the output power and efficiency. Both the transverse flux type switched reluctance generator (TFSRG) and the TFPMRG are designed using 3-D finite-element analysis (FEA) and a torque equation called the D-2L method. Finally, the design results of the TFSRG and TFPMRG are confirmed with 3-D FEA. According to the results, the output power and efficiency of TFPMRG are higher than those of TFSRG.

Mutually converted arc–line segment-based SLAM with summing parameters

This paper presents a mutually converted arc–line segment-based simultaneous localization and mapping (SLAM) algorithm by distinguishing what we call the summing parameters from other types. These redefined parameters are a combination of the coordinate values of the measuring points. Unlike most traditional features-based simultaneous localization and mapping algorithms that only update the same type of features with a covariance matrix, our algorithm can match and update different types of features, such as the arc and line. For each separated data set from every new scan, the necessary information of the measured points is stored by the small constant number of the summing parameters. The arc and line segments are extracted according to the different limit values but based on the same parameters, from which their covariance matrix can also be computed. If one stored segment matches a new extracted segment successfully, two segments can be merged as one whether the features are the same type or not. The mergence is achieved by only summing the corresponding summing parameters of the two segments. Three simultaneous localization and mapping experiments in three different indoor environments were done to demonstrate the robustness, accuracy, and effectiveness of the proposed method. The data set of the Massachusetts Institute Of Technology (MIT) Computer Science and Artificial Intelligence Laboratory (CSAIL) Building was used to validate that our method has good adaptability.

Natural corners-based SLAM with partial compatibility algorithm

This article presents natural corner-based simultaneous localization and mapping (SLAM) using a new data association algorithm that achieves partial compatibility in a real unknown environment. In the proposed corners’ extraction algorithm, both the end points of an extracted line segment far away from the other segments and the intersection point of the two closer line segments are considered as corners. In data association, a partial compatibility algorithm obtaining a robust matching result with low computational complexity is proposed. This method divides all the extracted corners at every step into several groups. In each group, the local best matching vector between the extracted corners and the stored ones is found by joint compatibility, while the nearest feature for every new extracted corner is checked by individual compatibility. All these groups with the local best matching vector and the nearest feature candidate of each new extracted corner are combined, and its joint compatibility is checked with the linear matching time. The experimental results in an indoor environment with natural corners show the robust matching result and low computational complexity of the partial compatibility algorithm in comparison with individual compatibility nearest neighbor and joint compatibility branch and bound.