• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.345-348
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• 1997

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effecter of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.

• Smart Structures and Systems
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• v.14 no.4
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• pp.617-641
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• 2014

The energy constraint is still a common issue for the practical application of wireless sensors, since they are usually powered by batteries which limit their lifetime. In this paper, a practical compound energy efficiency strategy is proposed and realized in the implementation of a real time wireless sensor platform. The platform is intended for wireless structural monitoring applications and consists of three parts, wireless sensing unit, base station and data acquisition and configuration software running in a computer within the Matlab environment. The high energy efficiency of the wireless sensor platform is achieved by a proposed adaptive radio transmission power control algorithm, and some straightforward methods, including adopting low power ICs and high efficient power management circuits, low duty cycle radio polling and switching off radio between two adjacent data packets' transmission. The adaptive transmission power control algorithm is based on the statistical average of the path loss estimations using a moving average filter. The algorithm is implemented in the wireless node and relies on the received signal strength feedback piggybacked in the ACK packet from the base station node to estimate the path loss. Therefore, it does not need any control packet overheads. Several experiments are carried out to investigate the link quality of radio channels, validate and evaluate the proposed adaptive transmission power control algorithm, including static and dynamic experiments.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.6
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• pp.535-541
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• 2014

In this research, three degree-of-freedom parallel spherical robot is developed for an artificial eyeball. The proposed system is comprised of a moving and a base plate, three prismatic actuators, and a ball joint for an angular movement of the moving plate. The vector analysis is employed to investigate the relationship between positions of the actuators and a pose of the moving plate. The required ranges for every actuators are calculated using the derived inverse kinematics in regard to the combination of two different levels for the size of the system component. Then the size of every components is determined from the analyzed trend. PI controller is employed for the position control of the moving plate. Finally the proposed system is verified using an arbitrary path of the angular movement.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.137-146
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• 2021

When controlling manipulator, degree of freedom is lost in singularity so specific joint velocity does not propagate to the end effector. In addition, control problem occurs because jacobian inverse matrix can not be calculated. To avoid singularity, we apply Deep Deterministic Policy Gradient(DDPG), algorithm of reinforcement learning that rewards behavior according to actions then determines high-reward actions in simulation. DDPG uses off-policy that uses 𝝐-greedy policy for selecting action of current time step and greed policy for the next step. In the simulation, learning is given by negative reward when moving near singulairty, and positive reward when moving away from the singularity and moving to target point. The reward equation consists of distance to target point and singularity, manipulability, and arrival flag. Dual arm manipulators hold long rod at the same time and conduct experiments to avoid singularity by simulated path. In the learning process, if object to be avoided is set as a space rather than point, it is expected that avoidance of obstacles will be possible in future research.

• Journal of Forest and Environmental Science
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• v.38 no.4
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• pp.239-248
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• 2022

Forestry crane work in a forest harvester or forwarder is regarded as one of most hard work requiring a very high level of operation skill. The operator must handle two or more multi-axes joysticks simultaneously to control the multiple manipulators for maneuvering the crane-tip to its intended location. This study has been carried out to develop a crane-tip controller which can intuitively maneuver the crane-tip, resulting in improving the productivity by decreasing the technical difficulty of control as well as reducing the workload. The crane-tip controller consists of a single 2-axis joystick and a control algorithm run on microcontroller. Lab-scale forestry crane was constructed using electric cylinders. The crane-tip control algorithm has the crane-tip follow the waypoints generated on the given path considering the dead band region using LBO (Lateral Boundary Offset). A speed control gain to change the speed of relevant cylinders relatively is applied as well. By the P (Proportional) control within the control interval of 20 msec, the average error of crane-tip control on the predefined straight path turned out to be 14.5 mm in all directions. When the joystick is used the waypoints are generated in real time by the direction signal from the joystick. In this case, the average error of path control was 12.4 mm for straight up, straight forward and straight down movements successively at a certain constant speed setting. In the slant movement of crane-tip by controlling two axes of joystick simultaneously, the movement of crane-tip was controlled in the average error of 15.9 mm when the crane-tip is moved up and down while moving toward forward direction. It concluded that the crane-tip control was possible using the control algorithm developed in this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.585-594
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• 2000

The exact path following of an autonomous mobile robot in a factory and an unreliable environment has many disadvantages in case of a classical control algorithm. In this paper, a neural network control approach based on an error back propagation algorithm is proposed for controlling a mobile robot to follow a line installed on the road. Since not only the three recognized informations from three sensors attached on a mobile robot but also the ten detailed informations in non recognition area are learned with input patterns, a mobile robot moves smoothly an installed line in spite of non perception space. The mobile robot has an effect of error minimization with a short time till a destination. To test an effectiveness of the proposed controller, the two motor velocity changes which is affected from a moving angle change of a mobile robot are simulated with computer.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.204-216
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• 2006

Latest advances in hardware technology and state of the art of mobile robot and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. And mobile service robot requires the perception of its present position to coexist with humans and support humans effectively in populated environments. To realize these abilities, robot needs to keep track of relevant changes in the environment. This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace) is used in order to achieve these goals. This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object 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. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used to estimate the location of moving robot. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot. Its performance is verified by computer simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1402-1407
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• 2004

Moving a fragile object from an initial point to a goal location in minimum time without damage is pursued in this paper. In order to achieve the goal, first of all, the range of maximum acceleration and velocity are specified, which the manipulator can generate dynamically on the path that is planned a priori considering the geometrical constraints. Later, considering the impulsive force constraint of the object, the range of maximum acceleration and velocity are going to be obtained to keep the object safe while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of the acceleration and velocity. This time optimal trajectory planning can be applied for real applications and is suitable for not only a continuous path but also a discrete path.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.130.1-130
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• 2001

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effector of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded ...

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.570-575
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• 2000

This paper presents a delayed time path planning method of the Autonomous Mobile Robot using fuzzy logic controller for avoidance of obstacles in unknown environment. It is the objective of this paper to develop fuzzy control algorithms using delayed time techniques to deal with moving obstacles randomly. This control method gives the benefit of the collision free movement in real time and optimal path to the pre-settled goal. The computer simulations are demonstrated the effective of the suggested control method in obstacle avoidance.