• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.168-173
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• 2003

In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

• Science of Emotion and Sensibility
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• v.5 no.4
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• pp.67-75
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• 2002

The purpose of this study is to assess the ability of balance control in virtual moving surround stimulation using head mount display (HMD) device and force platform in patients with brain injury. Fifteen patients with stroke (mean age 54.47 yrs) and fifteen healthy normal persons participated. COP parameters were obtained total path distance, frequency of anterior-posterior and medial-lateral component by FFT analysis, weight-spectrum analysis in the two different conditions; (1) during comfortable standing with opened or closed eyes, (2) during virtual moving surround stimulation delivered using HMD with four different moving pattern. Moving patterns consisted of close-far, superior-inferior lilting (pitch) , right-left tilting (roll) and horizontal rotation (yaw) movement. In all parameters, the test-retest reliability was high. Also, the construct validity of virtual moving surround stimulation was excellent (p＜0.05). A posturographic balance assessment system equiped with virtual moving surround stimulation using HMD is considered clinically useful in evaluation of balance control in patients with brain injury.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.788-793
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• 2015

This paper proposes a path planning algorithm to reduce the inspection time of AOI (Automatic Optical Inspection) machines for SMT (Surface Mount Technology) in-line system. Since the field-of-view of the camera attached at the machine is much less than the entire inspection region of board, the inspection region should be clustered to many groups. The image acquisition time depends on the number of groups, and camera moving time depends on the sequence of visiting the groups. The acquired image is processed while the camera moves to the next position, but it may be delayed if the group includes many components to be inspected. The inspection delay has influence on the overall job time of the machine. In this paper, we newly considers the inspection delay time for path planning of the inspection machine. The unified approach using genetic algorithm is applied to generates the groups and visiting sequence simultaneously. The chromosome, crossover operator, and mutation operator is proposed to develop the genetic algorithm. The experimental results are presented to verify the usefulness of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.601-606
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• 1998

In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1014-1020
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• 1990

Iterative algorithms for detecting the collision of convex objects whose motion is characterized by a path in configuration space are described. They use as an essential substep the computation of the distance between the two objects. When the objects are polytopes in either two or three dimensional space, an algorithm is given which terminates in a finite number of iterations. It determines either that no collision occurs or the first collision point on the path. Extensive numerical experiments for practical problems show that the computational time is short and grows only linearly in the total number of vertices of the two polytopes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.415-425
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• 2019

This study proposes a new approach to control Moving Stuff Action Through Iterative Learning robot with dual arm for smart factory. When robot moves object with dual arm, not only position of each hand but also contact force at surface of an object should be considered. However, it is not easy to determine every parameters for planning trajectory of the an object and grasping object concerning about variety compliant environment. On the other hand, human knows how to move an object gracefully by using eyes and feel of hands which means that robot could learn position and force from human demonstration so that robot can use learned task at variety case. This paper suggest a way how to learn dynamic equation which concern about both of position and path.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.256-261
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• 2005

In this research, we propose a path-planning algorithm for an autonomous mobile robot using geographical information, under the condition that the robot moves in unknown environment. All image inputted by camera at every sampling time are analyzed and geographical elements are recognized, and the geographical information is embedded in environmental map. The geographical information was transformed into 1-dimensional evaluation value that expressed the difficulty of movement for the robot. The robot goes toward the goal searching for path that minimizes the evaluation value at every sampling time. Then, the path is updated by integrating the exploited information and the prediction on unexploited environment. We used a sensor fusion method for improving the mobile robot dead reckoning accuracy. The experiment results that confirm the effectiveness of the proposed algorithm on the robot's reaching the goal successfully using geographical information are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.44.5-44
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• 2001

This paper proposes the algorithm which a mobile robot tracks the object captured by ultrasonic sensors of the robot and automatically generates a path according to the object In the proposed algorithm, a robot detects movements of the object as using ultrasonic sensors and then the robot follows the moving object. This algorithm simplifies robot path planning. The eight ultrasonic sensors on the robot capture distances between the robot and objects. The robot detects the movements of the object by using the changes of the distances captured by ultrasonic sensors. The target position of the robot is determined as the position of the detected moving object. The robot follows the object according to this movement strategy. The effectiveness of the proposed algorithm is verified through experiments.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.10-16
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• 2006

In this paper, moving a fragile object from an initial point to a specific location in the minimum time without damage is studied. In order to achieve this goal, initially, the maximum acceleration and velocity ranges are specified. These ranges can be dynamically generate on the planned path by the manipulator. The path can be altered by considering the geometrical constraints. Later, considering the impulsive force constraint on the object, the range of maximum acceleration and velocity are obtained to preserve object safety while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of acceleration and velocity. This time-optimal trajectory planning can be applied to real applications and is suitable for both continuous and discrete paths.