• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1927-1932
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• 2003

In a previous study, the authors have proposed the Cooperative Collision Avoidance (CCA) method which enables mobile robots to cooperatively avoid collisions, by extending the concept of the Velocity Obstacle to multiple robot systems. The method introduced an evaluation function considering an operation objective so that each robot can choose the velocity which optimizes the function. As the evaluation function could be of an arbitrary type, this method is applicable to a wide variety of tasks. However, it complicates the optimization of the function especially in real-time. In addition, construction of the evaluation function requires an operation objective of the other robot which is very hard to obtain without communication. In this paper, the CCA method is improved considering such problems for implementation. To decrease computational costs, the previous method is simplified by introducing two essential assumptions. Then, by treating the desired direction of locomotion for each robot as the operation objective, an operation objective estimator which estimates the desired direction of the other robot is introduced. The only measurement required is the other robot's relative position, since the other information can be obtained through the estimation. Hence, communicational devices that are necessary for most other cooperative methods are not required. Moreover, mobile robots employing the method can avoid collisions with uncooperative robots or moving obstacles as well as with cooperative robots. Consequently, this improved method can be applied to general dynamic environments consisting of various mobile robots.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.9-16
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• 2006

The Mobile robots are increasingly being used to perform tasks in unknown environments. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. An algorithm has been developed for robots which explore the environment to measure the physical properties (dust in this paper). While the robot is moving, it measures the amount of dust and registers the value in the corresponding grid cell. The robot moves from local maximum to local minimum, then to another local maximum, and repeats. To reach the local maximum or minimum, simple gradient following is used. Robust estimation of the gradient using perturbation/correlation, which is very effective when analytical solution is not available, is described. By introducing the probability of each grid cell, and considering the probability distribution, the robot doesn't have to visit all the grid cells in the environment still providing fast and efficient sensing. The extended algorithm to coordinate multiple robots is presented with simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.6-41
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• 2001

As autonomous mobile robot become more widely used in industry, the importance of navigation system is rising, But eh primary method of locomotion is with wheels, which cause man problems in controlling tracked mobile robots. In this paper, we discuss the used navigation control of tracked mobile robots with multiple sensors. The multiple sensors are composed of ultrasonic wave sensors and vision sensors. Vision sensors gauge distance using a laser and create visual images, to estimate robot position. The 80196 is used at close range and the vision board is used at long range. Data is managed in the main PC and management is distributed to ever sensor. The controller employs fuzzy logic.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1172-1177
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• 2003

In this paper, we propose an obstacle avoidance technique in trajectory tracking of nonholonomic wheeled mobile robots. Input-output linearized backstepping controller is used in trajectory tracking, and repulsive type control input for obstacle avoidance is added to it. The added input is generated by fuzzy logic. And we do not add the two inputs directly but combine them via fuzzy logic, which determines the ratings of each input. Some simulations are performed to show that with the proposed algorithm, the mobile robot can track its reference trajectory even if there are multiple obstacles on the trajectory of robot.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2189-2192
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• 1998

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which form from simple local rules to complex global intelligence. Here, we propose an architecture of neural network learing with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigates in a group. As results of the simulations, the optimum weights are obtained in real time, which not only prevent from the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.118-123
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• 2022

We implemented a real-time cloud robotics application by offloading robot navigation engine over to 5G Mobile Edge Computing (MEC) sever. We also ran a fleet management system (FMS) in the server and controlled the movements of multiple robots at the same time. The mobile robots under the test were connected to the server through 5G SA network. Public 5G network, which is already commercialized, has been temporarily modified to support this validation by the network operator. Robot engines are containerized based on micro-service architecture and have been deployed using Kubernetes - a container orchestration tool. We successfully demonstrated that mobile robots are able to avoid obstacles in real-time when the engines are remotely running in 5G MEC server. Test results are compared with 5G Public Cloud and 4G (LTE) Public Cloud as well.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.93-102
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• 2007

It is essential to estimating positions of multiple robots in order to perform cooperative task in common workspace. Accordingly, we propose a new approach of cooperative localization for multiple robots utilizing correlation among GPS errors in common workspace. Assuming that GPS data of individual robot are correlated strongly as the distance among robots are close, it is confirmed that the proposed method provides improved localization accuracy. In addition, we define two operational parameters to apply proposed method in multiple robot system. With mentioned two parameters, we present a practical solution to accumulated position error in traveling long distance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.124-130
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• 2005

Obstacle avoidance of underwater robots based on a modified virtual force field algorithm is proposed in this paper. The VFF(Virtual Force Field) algorithm, which is widely used in the field of mobile robots, is modified for application to the obstacle avoidance of underwater robots. This Modified Virtual Force Field(MVFF) algorithm using the fuzzy lgoc can be used in moving obstacles avoidance. A fuzzy algorithm is devised to handle various situations which can be faced during autonomous navigation of underwater robots. The proposed obstacle avoidance algorithm has ability to handle multiple moving obstacles. Results of simulation show that the proposed algorithm can be efficiently applied to obstacle avoidance of the underwater robots.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.114-120
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• 2007

This paper introduces a mobile robotic system being developed for urban search and rescue. In order to search human victims in narrow spaces, we developed two types of serially linked mobile robots, named KAEROT-Centipede and KAEROT-SnakeTV1, that can climb over large vertical steps or travel inside narrow vertical pipes. To send such mobile robots to the disaster areas coping with large obstacles, we also developed a assistant mobile robot, named KAEROT-QuadTrack, that has 4 articulated track modules. This paper describes the mechanical structure and control architecture of the serially linked mobile robots and the supporting configuration for torque reduction of the assistant mobile robot during spinning motion that usually requires large driving torque. The experimental results show that such robotic systems have good mobility over the various terrains in disaster areas.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.384-389
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• 2003

We propose a hierarchically structured navigation algorithm for multiple mobile robots under unknown dynamic environment based on fussy-neural algorithm. The proposed algorithm consists of two basic layers. The lower layer consists of two parts such as fuzzy algorithm for goal approach and fuzzy-neural algorithm for obstacle avoidance. The upper layer which is basically fuzzy algorithm adjusts the magnitude of the weighting factor depending on the environmental situation. In addition, The proposed algorithm provides an efficient method to escape local mimimum points as shown in the simulation result. The efficacy of the proposed method is demonstrated via some simulations.