Browsing by Author "Young, Kuu-Young"

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A hybrid of fuzzy theory and quadratic function for estimating and refining transmission map
(2019-01-01)
Jhang, Jyun-Yu
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Lin, Cheng-Jian
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Young, Kuu-Young
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Lin, Chin-Teng
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電控工程研究所
In photographs captured in outdoor environments, particles in the air cause light attenuation and degrade image quality. This effect is especially obvious in hazy environments. In this study, a fuzzy theory is proposed to estimate the transmission map of a single image. To overcome the problem of oversaturation in dehazed images, a quadratic-function-based method is proposed to refine the transmission map. In addition, the color vector of the atmospheric light is estimated using the top 1% of the brightest light area. Finally, the dehazed image is reconstructed using the transmission map and the estimated atmospheric light. Experimental results demonstrate that the proposed hybrid method performs better than the other existing methods in terms of color oversaturation, visibility, and quantitative evaluation.
A novel teaching and training system for industrial applications based on augmented reality
(1970-01-01)
Young, Kuu-Young
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Cheng, Shu-Ling
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Ko, Chun-Hsu
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Su, Yu-Hsuan
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Liu, Qiao-Fei
Along with the high demand on automation, more industrial robot manipulators are being introduced to factories. In addition to their manufacturing, it is also very crucial on the deployment and training of the robots. It thus solicits the development of new types of manipulative devices and methods for tackling these tasks of high complexity. To achieve effective task execution, this paper proposes a novel AR-based teaching and training system, along with several assistive strategies. The technique of augmented reality (AR), which combines virtual objects with real scenes, is used for providing visual immersion. The assistive strategies, including that of collision-free path planning, occlusion effect removal, and visual guidance, are designed to ease the user from the load during the complicated teaching process. We conduct a series of experiments for performance evaluation. Questionnaires based on the system usability scale are also administered to obtain feedback from users.
A STUDY OF FITTS' LAW ON GOAL-DIRECTED AIMING TASK WITH MOVING TARGETS
(2011-08-01)
Chiu, Tien-Ting
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Lin, Chun-Ling
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Young, Kuu-Young
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Lin, Chin-Teng
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Hsu, Shang-Hwa
Most research based on Fitts' law define a log-linear relationship between temporal and spatial accuracy in goal-directed aiming tasks using stationary targets. Whether this relationship holds or not when the targets have varying velocities, and how the behavioral strategies and physical activities may change accordingly are of interest. The aim of this study was to investigate the relationship between temporal and spatial accuracy in goal-directed aiming tasks with moving targets. Participants were asked to aim at two target widths using a joystick. Results demonstrated that in a goal-directed aiming task there was a negative effect on performance when target velocity was increased or target width was decreased. Participants moved faster and then made more systematic errors in a high-velocity target condition. Results may be applicable to the complex perceptual-motor behavior of people who perform tasks using computers.
Active and Passive Control of Walk-Assist Robot for Outdoor Guidance
(2013-06-01)
Ko, Chun-Hsu
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Young, Kuu-Young
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Huang, Yi-Che
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Agrawal, Sunil Kumar
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電機工程學系
In the currently aging society, walk-assist robots can play an important role in improving the activities of daily living of the elderly. In this paper, we propose a robot walking helper with both passive and active control modes for guidance. From the perspective of human safety, the passive mode adopts a braking control law on the wheels to differentially steer the vehicle. However, if the user walks uphill in the outdoor environment, external forces need to be supplied to the human-walker system. In this paper, we add an active mode to guide the user in situations where the passive control mode alone with user-applied forces is not adequate for guidance. The theory of differential flatness is used to plan the trajectory of control gains within the proposed scheme of the controller. Since the user input force and slope angle of the path are not known a priori, the theory of model predictive control is used to periodically compute the trajectory of these control gains. The simulation and experiment results show that the walk-assist robot, along with the structure of this proposed control scheme, can guide the user to a goal on a slope effectively.
Adjusting Electrode Potentials to Compensate Thermal/Tissue Effects in Deep Brain Stimulation via Finite Element Electromagnetic Analysis
(2010-06-01)
Chuang, Wei-Yi
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Chao, Paul C. -P.
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Young, Kuu-Young
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影像與生醫光電研究所
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電機工程學系
The proposed method is intended to adjust the electrode potentials used in deep brain stimulation (DBS) with the consideration of both tissue transform and thermal effects caused by stimulation. During a typical DBS process, it is essential, for an effective treatment, to control the stimulation strength and region with varied applied electrode potentials. Some previous studies have been devoted for numerical simulations to find suitable electrode voltage levels for pre-desired stimulated strength and region. These studies consider only one of the two complexity factors due to the intrusion of the DBS lead: 1) a layer of extracellular fluid and giant cell often formed around the DBS leads, called the peri-electrode space and 2) thermal effects. These two factors should both be considered in finite element electromagnetic analysis (FEA), which provides the means to adjust electrode potential for the originally-desired DBS region-called the volume of tissue activated (VTA). Simulation results show that there should be a limiting stimulation voltage to meet the temperature constraint.
An Adaptive Upper-Arm EMG-Based Robot Control System
(2010-09-01)
Liu, Hsiu-Jen
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Young, Kuu-Young
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電機工程學系
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Department of Electrical and Computer Engineering
The human-assisting robot can be helpful for improving the life quality of the disabled and elderly. As Electromyography (EMG) is a physiological signal generated during muscle contraction, it implicates, to certain extent, the human intention for movement, and is thus very suitable to serve as the control signal for the assisting robot. In this paper, we develop an upper-arm EMG-based robot control system, which provides a natural and intuitive manipulation. To satisfy the demand of real-time control, we propose a simple and effective method for the mapping between the upper-arm EMG signal and corresponding movement. However, due to the fuzziness inherent in the EMG signals, which are time-varying and highly nonlinear, the tuning for system parameters is not that straightforward. We therefore employ the concept of fuzzy system to find proper parameters that better suit for the individual users. To provide better adaptive capability, we propose using the adaptive neuro-fuzzy inference system (ANFIS) to realize the fuzzy system. We perform a series of experiments to demonstrate the effectiveness of the proposed adaptive upper-arm EMG-based robot control system.
An SOM-based algorithm for optimization with dynamic weight updating
(2007-06-01)
Chen, Yi-Yuan
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Young, Kuu-Young
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電控工程研究所
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Institute of Electrical and Control Engineering
The self-organizing map (SOM), as a kind of unsupervised neural network, has been used for both static data management and dynamic data analysis. To further exploit its search abilities, in this paper we propose an SOM-based algorithm (SOMS) for optimization problems involving both static and dynamic functions. Furthermore, a new SOM weight updating rule is proposed to enhance the learning efficiency; this may dynamically adjust the neighborhood function for the SOM in learning system parameters. As a demonstration, the proposed SOMS is applied to function optimization and also dynamic trajectory prediction, and its performance compared with that of the genetic algorithm (GA) due to the similar ways both methods conduct searches.
APPLYING WAVE-VARIABLE-BASED SLIDING MODE IMPEDANCE CONTROL FOR ROBOT TELEOPERATION
(2011)
Liu, Hsiu-Jen
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Young, Kuu-Young
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電機工程學系
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Department of Electrical and Computer Engineering
The wave variable approach has the appealing features of not requiring a priori knowledge on both time delay and master/slave plants and simplicity in parameter adjustment, when applied for robot teleoperation. However, its current applications are mainly related to tasks involving position tracking. In this paper, we propose integrating the wave variable approach with the sliding mode impedance controller, so that it can be further applied for robot compliance tasks, in which simultaneous control of both position and force are commanded and contact with the environment is inevitable. We start with the validation of the stability of the proposed wave-variable-based sliding mode impedance control scheme. For demonstration, we apply the proposed system to perform the command-following compliance task in both simulation and experiment.
Collision-Free Guidance for Passive Robot Walking Helper
(2012-01-01)
Huang, Yi-Che
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Wu, Cheng-Je
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Ko, Chun-Hsu
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Young, Kuu-Young
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電子工程學系及電子研究所
With the increase of aging population, robot walking helpers have been developed to assist the elderly in their daily life. Based on our previous work, a passive robot walking helper (named i-Go) equipped with a guidance strategy, in this paper, we further propose a navigation scheme for obstacle avoidance. The proposed scheme first locates the waypoints in the collision-free areas, and then guides the i-Go to reach the desired target with the specified orientation. Simulations and experiments are performed to verify the effectiveness of the proposed scheme. The results demonstrate that the scheme can guide the user to avoid the obstacles and successfully approach the target with the specified orientation.
Computerized Stimulation Parameter Adjustment of Deep Brain Stimulation Minimizing Side Effects and Power Consumption for Parkinson\'s Disease
(2014-01-01)
Chuang, Wei-Yi
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Chao, Paul Chang-Po
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Young, Kuu-Young
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Deep brain stimulation (DBS) is broadly applied for neuropsychiatric diseases and thus determining its mechanism is of interest, especially in terms of the neural structure surrounding the DBS probe and the volume of tissue activated (VTA) during DBS. For re-operations for battery replacement, a major issue is reducing treatment power consumption without compromising clinical benefits. To avoid side effects and to minimize power consumption, optimized adjustment of the stimulation parameters is required. This study thus proposes a scheme for determining the optimal stimulation parameters. An electromagnetic finite element model for a patient-specific physiological brain model is first established using magnetic resonance imaging (MRI) data. Using finite element analysis (FEA), varied stimulation parameters are applied to the electromagnetic model for VTA estimation. Optimal electrode contact(s) are selected based on the estimated VTA to avoid side effects. Moreover, a nonlinear programming method for optimizing the stimulation voltage and the pulse width is applied to minimize power consumption in DBS. The effectiveness of the model parameters was verified using five Parkinson\'s disease patients. The results demonstrate that the estimates of the VTA are consistent with the observations within the desired region of the brain while avoiding side effects and reducing power consumption by 13% on average. The proposed method allows clinicians and researchers to efficiently select the optimal stimulation parameters. Moreover, it provides valuable information for closed-loop stimulation protocols in DBS.
Computing stimulation voltage in a bipolar electrode configuration to avoid side effects during deep brain stimulation
(2015-09-01)
Chuang, Wei-Yi
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Chao, Paul C. -P.
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Chen, Shin-Yuan
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Tsai, Sheng-Tzung
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Young, Kuu-Young
Deep brain stimulation (DBS) in the subthalamic nucleus (STN) has been applied for advanced Parkinson\'s disease (PD). In clinical practices, monopolar configuration is often utilized based on clinical efficiency. Meanwhile, the volume of tissue activated (VTA) by DBS is estimated for controlling and/or limiting the stimulated region. However, side effects like dyskinesia and tremor were accompanied during stimulation. Most studies had found that bipolar stimulation is an alternative approach for side effects avoidance. The goal of this paper is to develop a quantified relationship of stimulation voltage from monopolar to bipolar configuration to improve neural stimulation. In this paper, an electromagnetic finite element model is first built for a patient-specific physiological brain model, which is established by magnetic resonance imaging (MRI) data. The model is then used for finite element analysis (PEA) to estimate VTA with varied electrode voltage in monopolar and bipolar configurations. With the goals to avoid side effects and achieve symptoms suppression, the stimulation voltage of bipolar configuration is successfully computerized based on the electromagnetic PEA simulations. Experiments are conducted successfully to validate simulation results. (C) 2015 Elsevier B.V. All rights reserved.
Cooperative Carrying Control for Multi-Evolutionary Mobile Robots in Unknown Environments
(2019-03-06)
Jhang, Jyun-Yu
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Lin, Cheng-Jian
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Young, Kuu-Young
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電控工程研究所
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Institute of Electrical and Control Engineering
This study provides an effective cooperative carrying and navigation control method for mobile robots in an unknown environment. The manager mode switches between two behavioral control modes-wall-following mode (WFM) and toward-goal mode (TGM)-based on the relationship between the mobile robot and the unknown environment. An interval type-2 fuzzy neural controller (IT2FNC) based on a dynamic group differential evolution (DGDE) is proposed to realize the carrying control and WFM control for mobile robots. The proposed DGDE uses a hybrid method that involves a group concept and an improved differential evolution to overcome the drawbacks of the traditional differential evolution algorithm. A reinforcement learning strategy was adopted to develop an adaptive WFM control and achieve cooperative carrying control for mobile robots. The experimental results demonstrated that the proposed DGDE is superior to other algorithms at using WFM control. Moreover, the experimental results demonstrate that the proposed method can complete the task of cooperative carrying, and can realize navigation control to enable the robot to reach the target location.
Design of force-reflection joystick system for VR-Based simulation
(2007-09-01)
Lin, Wei-Ching
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Young, Kuu-Young
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電控工程研究所
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Institute of Electrical and Control Engineering
In this paper, we develop a force-reflection joystick system for VR-based simulation, including a 2-DOF joystick and the related software. The developed force-reflection joystick, as a kind of haptic device, provides two-way communication in both position and force, and is very helpful for the user to interact with a simulation system. By considering the main factors in designing a force-reflection joystick, we build the joystick to be with the bandwidth, precision, and output torque comparable to the advanced commercial joystick. We also perform workspace analysis, system identification, and system modeling to better connect the joystick with the simulation system. To make it suitable for various applications, the software is developed to generate virtual motion constraints, so that the joystick is confined to operate within the workspace that corresponds to task requirements. In other words, the joystick may behave like a manipulative device specific for the given task. For demonstration, in experiments, we use the developed joystick system to emulate a virtual manual gearshift system.
Development of a 3D AR-Based Interface for Industrial Robot Manipulators
(2018-01-01)
Su, Yu-Hsuan
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Chen, Chun-Yung
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Cheng, Shu-Ling
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Ko, Chun-Hsu
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Young, Kuu-Young
Along with the progress in automation and Industry 4.0, the use of industrial robots becomes much more popular. Meanwhile, the conventional manipulative devices, such as teaching pendant and joystick, are not intuitive enough and very time-consuming for task teaching. In facing more complicated tasks these days, it then induces high cost and demands experts with proper training. This paper thus aims to develop an intuitive manipulatory interface for assistance in simplifying the teaching process. We propose a wireless 3D manipulation system based on augmented reality (AR) with the tablet PC as the platform. The system allows the user to govern the movement of a real robot in a 3D space via a virtual one generated through AR We also develop several intelligent tools to assist the manipulation, so that accurate and collision-free path can be generated for the robot to follow for task execution. In addition, the system can also be used for offline training, which yields salient training effect for the operator. Experiments are executed to demonstrate the effectiveness of the proposed system, and questionnaires conducted to investigate user's response.
Development of Intention Detection and Control System for Robot Walking Helper
(2016-01-01)
Huang, Zih-Lun
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Jhuang, Cing-Hao
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Ko, Chun-Hsu
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Young, Kuu-Young
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電機工程學系
In current aging society, robot walking helpers play an important role in improving the activities of daily living of the elders. In this paper, we develop an intention detection and passive control system for a robot walking helper. For safe manipulation, the robot can obtain user's walking intention by identifying the foot image and adopt a braking control law on the wheels to differentially steer the robot. Experiments are conducted to demonstrate the effectiveness of the proposed system.
Development of Upper-Limb Exoskeleton Simulator for Passive Rehabilitation
(2014)
Huang, Jian-Bin
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Hong, Jing-Chen
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Young, Kuu-Young
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Ko, Chun-Hsu
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電子工程學系及電子研究所
Due to the progress in robotics, exoskeleton has been applied in rehabilitation for those enduring damage in central nervous system, spinal cord, and others. In this kind if application, the main concern is the safety of the user, as he/she is closely connected to the exoskeleton. That means the developed exoskeleton needs be carefully evaluated in each aspect of the design. For this purpose, we develop a simulator for general types of upper-limb exoskeletons. To make it realistic, this simulator considers kinematics, dynamics, path planning, control, and also human factor. For demonstration, we apply it to our developed upper-limb exoskeleton, HAMEXO-I, which is designed for passive rehabilitation.
EEG correlates of haptic feedback in a visuomotor tracking task
(2012-05-01)
Lin, Chun-Ling
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Shaw, Fu-Zen
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Young, Kuu-Young
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Lin, Chin-Teng
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Jung, Tzyy-Ping
This study investigates the temporal brain dynamics associated with haptic feedback in a visuomotor tracking task. Haptic feedback with deviation-related forces was used throughout tracking experiments in which subjects' behavioral responses and electroencephalogram (EEG) data were simultaneously measured. Independent component analysis was employed to decompose the acquired EEG signals into temporally independent time courses arising from distinct brain sources. Clustering analysis was used to extract independent components that were comparable across participants. The resultant independent brain processes were further analyzed via time-frequency analysis (event-related spectral perturbation) and event-related coherence (ERCOH) to contrast brain activity during tracking experiments with or without haptic feedback. Across subjects, in epochs with haptic feedback, components with equivalent dipoles in or near the right motor region exhibited greater alpha band power suppression. Components with equivalent dipoles in or near the left frontal, central, left motor, right motor, and parietal regions exhibited greater beta-band power suppression, while components with equivalent dipoles in or near the left frontal, left motor, and right motor regions showed greater gamma-band power suppression relative to non-haptic conditions. In contrast, the right occipital component cluster exhibited less beta-band power suppression in epochs with haptic feedback compared to non-haptic conditions. The results of ERCOH analysis of the six component clusters showed that there were significant increases in coherence between different brain networks in response to haptic feedback relative to the coherence observed when haptic feedback was not present. The results of this study provide novel insight into the effects of haptic feedback on the brain and may aid the development of new tools to facilitate the learning of motor skills. (C) 2012 Elsevier Inc. All rights reserved.
Effective Control for an Upper-Body Exoskeleton Robot Using ANFIS
(2016)
Huang, Jian-Bin
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Young, Kuu-Young
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Ko, Chun-Hsu
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
In responding to the coming of an aging society, the exoskeleton robot is of focus, which provides assistance for people with locomotive problems. As the exoskeleton robot is worn by the user, the interaction in between induces several severe challenges, including adequate controller design. To deal with the nonlinearity involved during motion governing, in this paper, we take advantage of the capability of the adaptive network-based fuzzy inference system (ANFIS), and propose an ANFIS-PID controller for the exoskeleton type of robot. Especially, we apply it to a 2-DOF upper-body exoskeleton robot, HAMEXO-I, developed in our laboratory. With the proposed controller, we intend to let HAMEXO-I adaptable for a wide range of users, and able to serve for simple daily activities. Experiments are performed to demonstrate its effectiveness.
Effective Maneuver for Passive Robot Walking Helper Based on User Intention
(2015-10-01)
Hsieh, Yi-Hung
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Young, Kuu-Young
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Ko, Chun-Hsu
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電機工程學系
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Department of Electrical and Computer Engineering
In response to an aging society, a robot walking helper has come up as a research focus. To be practical for use in daily lives for the elderly, it should be able to follow user intention during maneuver and provide motion assistance when demanded. As quite a number of guidance schemes have been proposed, the studies on maneuver are comparatively few. This paper thus proposes a maneuvering system for the passive type of robot walking helper based on user intention. The proposed system first recognizes motion intention from user-applied force and hip rotation, and then utilizes an assistive control strategy to generate proper braking torque for effective maneuver. Experiments in a real environment are conducted for demonstration.
Effective manipulation for a multi-DOF robot manipulator in laboratory environments
(2013)
Hsieh, Mu-Cheng
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Young, Kuu-Young
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電機學院
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College of Electrical and Computer Engineering
Robots are expected to enter human environments soon, and many challenging problems may then emerge when facing uncertain and varying environments. Among the challenges, one issue of great interest is how they can be effectively operated for task execution. If a robot is not to be controlled by detailed analysis and program coding, one appealing alternative is to provide a kind of manipulation system which enables the user to operate the robot naturally and efficiently. This idea has motivated us to develop an effective manipulation system for multi-degree of freedom (DOF) robot manipulators based on a 6-DOF haptic device. In this article, we focus on the laboratory environment, which is somewhat organized, but still demands sophisticated human manipulation. The proposed manipulation system, aimed for 3-D applications, provides two kinds of assistance. One is to enhance the linkage between the user and robot manipulator via the haptic clue. The other is to guide the movement of the user during task execution via a set of virtual tools, e. g., a ruler. We also propose a method for achieving smooth force rendering in manipulation, especially during the transition between two consecutive manipulations for guidance. For performance evaluation, this system is employed to conduct experiments in the chemical laboratory, which involve delicate and challenging maneuvers.