• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.818-829
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• 2003

A cooperating control algorithm for two nonholonomic mobile robots is proposed. The task is composed of collision avoidance against obstacles and carrying a ladder. The front robot and the rear robot are called the leader and the follower, respectively. Each robot has a nonholonomic constraint so it cannot move in perpendicular directions. The environment is initially supposed to be unknown except target position. The torque that drives leader is determined by distance between the leader and the target position or the distance between it and the obstacles. The torque by target is attractive and the torque by obstacles is repulsive. The two mobile robots are supposed to be connected by link that can be expanded and contracted. The follower computes its torque using position and orientation information from the leader by communication. Simulation results show that the robots can drive to target position without colliding into the obstacles and maintain the distance in the allowable range.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.119-125
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• 2008

This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.918-925
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• 2017

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.392-397
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• 2020

Unmanned robots are very useful for autonomous security systems. These robots navigate autonomously move in a large area for surveillance. It is very important for robots that cover such a wide area to communicate with a control systems. Therefore, the control system needs various communication methods to check the status of the robot and send/receive messages. In addition, it is necessary to provide an easy interface for the user to send security mission commands to the robot. In this paper, we propose a control system based on a variety of communication techniques to perform security by safely communicating with a number of robots in a wide area space. The proposed system designed for considering user UI, data storage and management, and shows usability by constructing it in a real environment.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.570-576
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• 2007

This paper presents a hexagon-based Q-leaning algorithm to find a hidden targer object with multiple robots. An experimental environment was designed with five small mobile robots, obstacles, and a target object. Robots went in search of a target object while navigating in a hallway where obstacles were strategically placed. This experiment employed two control algorithms: an area-based action making (ABAM) process to determine the next action of the robots and hexagon-based Q-learning to enhance the area-based action making process.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1073-1078
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• 2012

This paper deals with the trajectory planning of multi agent robots using complex potential theory for robot soccer. The complex potential theory is introduced, then the circle theorem is used to avoid obstacles, and the vortex pair is used to make precise kicking direction of robot. Various situations of robot soccer are simulated and the effect of vortex strength and the speed of robots are discussed and the better way to avoid obstacles and to kick the precise direction is found. The feasibilities of complex potential theory to apply for the multi agent robots are successful.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.2
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• pp.14-20
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• 1999

In this paper, we discuss about implementation of a wireless communication system for a distributed autonomous robotic system. In order to achieve cooperative behavior among mobile robots, it is required to perform communication. Based on this requirements, we examined to the application in a wireless communication system used by mobile robots. This paper describes a conceptual and experimental framework which provides a distributed control architecture for the study of interactions between multiple mobile robots.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.59-59
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• 2000

In this paper, we present a framework for modeling and control of multiple mobile robots which cowork within a bounded workspace and limited resources. To achieve this goal, we adopt a formalism of discrete event system and supervisory control theory based on Petri nets. We can divide our whole story into two parts: first, we search the shortest path using the distance vector algorithm, and then we construct the control scheme from which a number of mobile robots can work within a bounded workspace without any collision. The use of Petri net modeling allows us In synthesize a controller which achieves a control specification for the desired closed-loop behavior efficiently. Finally, the usefulness of the proposed Petri net formalism is illustrated by a simulation study.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.