• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.16-20
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• 1999

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.138-142
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• 2007

This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the: given environment. The suggested method is applied to the control of $KUKA^{TM}$, a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of $MatLab^{TM}\;and\;RecurDyn^{TM}$.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.455-464
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• 1994

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMG signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.137-145
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• 2008

We present the initial results of on-going research for building a novel Mobile Haptic Interface (MHI) that can provide an unlimited haptic workspace in large immersive virtual environments. When a user explores a large virtual environment, the MHI can sense the position and orientation of the user, place itself to an appropriate configuration, and deliver force feedback, thereby enabling a virtually limitless workspace. Our MHI (PoMHI v0.5) features with omnidirectional mobility, a collision-free motion planning algorithm, and force feedback for general environment models. We also provide experimental results that show the fidelity of our mobile haptic interface.

• Smart Structures and Systems
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• v.33 no.4
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• pp.291-300
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• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.

• Journal of the Ergonomics Society of Korea
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• v.6 no.2
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• pp.19-28
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• 1987

If an error occurs in the automatic mode when the advanced teleoperator system performs a task in hostile environment, then the mode changes into the manual mode. The operation by program and the operation by hyman recover the error in the manual mode. The system resumew the automatic mode and continues the given task. In order to utilize the inverse kinematics as means of the operation by program in the manual mode, Lee and Nagamachi determined the end point of the robot trajectory planning which varied with the height of the task object recognized by a T.V monitor, solved the end point by the fuzzy set theory, and controlled the position of the robot hand by the inverse kinematics and the posture of the robot hand by the operation by human. But the operation by human did take a lot of task time because the position and the posture of the robot hand were separately controlled. To reduce the task time by human, this paper developes an error recovery expert system (ERES). The position of the robot hand is controlled by the inverse kinematics of the cartesian coordinate system to the end point which is deter- mined by the fuzzy set theory. The posture of the robot hand is controlled by the modulality of the robot hand's motion which is made by the posture of the task object. The knowledge base and the inference engine of the ERES is developed using the muLISP-86 language. The experimental results show that the average task time by human the ERES which was performed by the integration of the position and the posture control of the robot hand is shorter than that of the research, done by the preliminary experiment, which was performed by the separation of the position and the posture control of the robot hand. A further study is likely to research into an even more intelligent robot system control usint a superimposed display and digitizer which can present two-dimensional coordinate of the work space for the convenience of human interaction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.101-110
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• 2004

The robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, humans and robots need to be in close proximity to each other as much as possible. Moreover, it is necessary for their interactions to occur naturally. It is desirable for a robot to carry out human following, as one of the human-affinitive movements. The human-following robot requires several techniques: the recognition of the moving objects, the feature extraction and visual tracking, and the trajectory generation for following a human stably. In this research, a predictable intelligent space is used in order to achieve these goals. An intelligent space is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.117-124
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• 1989

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan`s method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMf signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1472-1488
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• 2019

Critical elements in the China's Lunar Exploration reside in that the lunar rover travels over the surrounding undetermined environment and it conducts scientific exploration under the ground control via teleoperation system. Such an interplanetary transportation mission teleoperation system belongs to the ground application system in deep space mission, which performs terrain reconstruction, visual positioning, path planning, and rover motion control by receiving telemetry data. It plays a vital role in the whole lunar exploration operation and its so-called trustworthy evidence must be assessed before and during its implementation. Taking ISO standards and China's national military standards as trustworthy evidence source, the net assessment model and net assessment method of teleoperation system are established in this paper. The multi-dimensional net assessment model covering the life cycle of software is defined by extracting the trustworthy evidences from trustworthy evidence source. The qualitative decisions are converted to quantitative weights through the net assessment method (NAM) combined with fuzzy analytic hierarchy process (FAHP) and entropy weight method (EWM) to determine the weight of the evidence elements in the net assessment model. The paper employs the teleoperation system for interplanetary transportation as a case study. The experimental result drawn shows the validity and rationality of net assessment model and method. In the final part of this paper, the untrustworthy elements of the teleoperation system are discovered and an improvement scheme is established upon the "net result". The work completed in this paper has been applied in the development of the teleoperation system of China's Chang'e-3 (CE-3) "Jade Rabbit-1" and Chang'e-4 (CE-4) "Jade Rabbit-2" rover successfully. Besides, it will be implemented in China's Chang'e-5 (CE-5) mission in 2019. What's more, it will be promoted in the Mars exploration mission in 2020. Therefore it is valuable to the development process improvement of aerospace information system.