• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.355-355
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• 2000

The position control accuracy of a robot manipulator is significantly deteriorated when a long arm robot is operated at a high speed. This paper presents a very simple sliding mode control which eliminates multiple mode residual vibration in a 개bot manipulator. The neural network is used to avoid that sliding mode condition is deviated due to the change of system parameter and disturbance. This paper is suggested control system which designed by sliding mode controller using neural network. The effectiveness of proposed scheme is demonstrated through computer simulation.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.689-702
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• 2019

This paper deals with the verification of the functions about mining robot, which is the system for developing deep seabed resources by applying V&V(verification and validation). In order to overcome water pressure of 500 bar and to travel on soft ground, and to operate in deep sea environment with bad conditions, it is necessary to develop a robot that can satisfy various deepsea conditions. A mining robot has been developed based on simulation based design and Multidisciplinary design optimization. In order to verify the developed robot, lab test and real sea test should be performed for various marine environment conditions. There are too many requirements to consider, such as space, time, cost, personnel, and environment to do performance test. So it is costly and time consuming for developing robot. In order to solve this problems, V&V technique was applied to mining robot. The stages of mining robot design, fabrication and commission were verified.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1463-1471
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• 2012

In this study, a 3-axis camera system design is proposed for application to an existing 2-axis surveillance robot. A camera-image-based target-tracking algorithm for this robot has also been proposed. The algorithm has been validated using a virtual simulation. In the algorithm, the heading direction vector of the camera system in the mobile surveillance robot is obtained by the position error between the center of the view finder and the center of the object in the camera image. By using the heading direction vector of the camera system, the desired pan and tilt angles for target-tracking and the desired roll angle for the stabilization of the camera image are obtained through inverse kinematics. The algorithm has been validated using a virtual simulation model based on MATLAB and ADAMS by checking the corresponding movement of the robot to the target motion and the virtual image error of the view finder.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.3
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• pp.29-36
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• 2005

With the rapid growth of the Internet, the Internet-based robot has been realized by connecting off-line robot to the Internet. However, because the Internet is often irregular and unreliable, the varying time delay in data transmission is a significant problem for the construction of the Internet-based robot system. Thus, this paper is concerned with the development of an Internet-based robot system, which is insensitive to the Internet time delay. For this purpose, the PPS (Position Prediction Simulator) is suggested and implemented on the system. The PPS consists of two parts : the robot position prediction part and the projective virtual scene part. In the robot position prediction part, the robot position is predicted for more accurate operation of the mobile robot, based on the time at which the user's command reaches the robot system. The projective virtual scene part shows the 3D visual information of a remote site, which is obtained through image processing and position prediction. For the verification of this proposed PPS, the robot was moved to follow the planned path under the various network traffic conditions. The simulation and experimental results showed that the path error of the robot motion could be reduced using the developed PPS.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.169-178
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• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2498-2504
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• 2009

The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.321-324
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement Beaming is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement loaming is different from supervised teaming in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement loaming algorithms like Q-learning do not require defining or loaming any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning(AMMQL) as an improvement of the existing Modular Q-Learning(MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.49-58
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• 2009

Top-down approach in the intelligent robot research has focused on the single object intelligence however, it has two weaknesses. One is that has a high cost and a long spending time of sensing, calculating and communications. The other is the difficulty of responding to react changes in the unpredictable environment. we propose the collective intelligence algorithm based on Bottom-up approach for improving these weaknesses and the applied agent model and verify by simulation. The Modified Flocking Algorithm proposed in this research is the algorithm which is modified version of the concept of the Flocking (Craig Reynolds) which is used to model the flocks, herds, and schools in the graphics or games, and simplified the operation of conventional Flocking algorithm to make it easy to apply for the number of group robots. We modeled the Boid agent and verified possibility collectivization of the Modified Flocking Algorithm by simulation. And We validated by the actual multiple mobile robot experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1780-1783
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• 2005

In this paper ZMP was considered in order to get a walking stability, so the gait in the stable domain was realized through putting the stability margin in the sole domain of a foot. It is assumed that the robot's legs have 12 joints to operate a open-loop drive and there was no external disturbance under walking phases, additionally, the robot is walking on the flat plane. It was observed that the robot's walking trajectory, locus of COM and ZMP after imposing the motion to each joint. For realizing the simulation considering ZMP and movement of mass center, it was checked if it is stable for the constraint robot model to walk in stability and the feasibility was estimated about its dynamic gait. Eventually it was shown that a constraint gait algorithm is able to realize. To verify the proper walking process, ZMP(Zero Moment Point) theory is applied and the simulation has been done by ADAMS.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.672-678
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• 2008

This paper proposes a new rehabilitation robot with upper and lower limb connections for gait training. As humans change a walking speed, their nervous systems adapt muscle activation patterns to modify arm swing for the appropriate frequency. By analyzing this property, we can find a relation between arm swinging and lower limb motions. Thus, the lower limb motion can be controlled by the arm swing for walking speed adaptation according to a patent's intension. This paper deals with the design aspects of the suggested gait rehabilitation robot, including a trajectory planning and a control strategy. The suggested robot is mainly composed of upper limb and lower limb devices, a body support system. The lower limb device consists of a slider device and two 2-dof footpads to allow walking training at uneven and various terrains. The upper limb device consists of an arm swing handle and switches to use as a user input device for walking. The body support system will partially support a patient's weight to allow the upper limb motions. Finally, we showed simulation results for the designed trajectory and controller using a dynamic simulation tool.