• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2019-2023
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• 2005

In this paper, an autonomous omni directional cleaning robot which recognizes an obstacle and a battery charger is introduced. It utilizes a robot vision, ultra sonic sensors, and infrared sensors information along with appropriate algorithm. Three omni-directional wheels make the robot move any direction, enabling a faster maneuvering than a simple track typed robot. The robot system transfers command and image data through Blue-tooth wireless modules to be operated in a remote place. The robot vision associated with sensor data makes the robot proceed in an autonomous behavior. An autonomous battery charger searching is implemented by using a map-building which results in overcoming the error due to the slip on the wheels, and camera and sensor information.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.3
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• pp.125-131
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• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.579-588
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• 1996

The purpose of this paper is to develop a method of Collision-Free Path Planning (CFPP) for an articulated robot. First, the configuration of the robot is built by a set of robot joint angles derived from robot inverse kinematics. The joint space, that is made of the joint angle set, forms a Configuration space (Cspcce). Obstacles in the robot workcell are also transformed into the Cobstacles using slice projection method. Actually the Cobstacles means the configurations of the robot causing collision with obstacles. Secondly, a connected graph, a kind of roadmap, is constructed by the free configurations in the Cspace, where the free configurations are randomly sampled from a free Cspace immune from the collision. Thirdly, robot paths are optimally determinant in the connected graph. A path searching algorithm based on $A^*$ is employed in determining the paths. Finally, the whole procedures for the CFPP method are shown for a proper articulated robot as an illustrative example.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.404-404
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• 2000

This paper presents a single vision-based sel(-localization method in an corridor environment. We use the Hough transform for finding parallel lines and vertical lines. And we use these cross points as feature points and it is calculated relative distance from mobile robot to these points. For matching environment map to feature points, searching window is defined and self-localization is performed by matching procedure. The result shows the suitability of this method by experiment.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1033-1041
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• 2003

A new visual tracking scheme is proposed for a mobile robot that tracks a moving object in 3D space in real time. Visual tracking is to control a mobile robot to keep a moving target at the center of input image at all time. We made it possible by simplifying the relationship between the 2D image frame captured by a single camera and the 3D workspace frame. To precisely calculate the input vector (orientation and distance) of the mobile robot, the speed vector of the target is determined by eliminating the speed component caused by the camera motion from the speed vector appeared in the input image. The problem of temporary disappearance of the target form the input image is solved by selecting the searching area based on the linear prediction of target motion. The experimental results have shown that the proposed scheme can make a mobile robot successfully follow a moving target in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.825-832
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• 2004

A small biped robot system is designed and implemented. The robot system consists of a mechanical robot body, a control system, a sensor system, and a user interface system. The robot has 12 dofs for two legs, 6 dofs for two arms, 2 dofs for a neck, so it has total 20 dofs to have dexterous motion capability. The implemented robot has the capability of performing intelligent actions such as playing soccer, resisting external forces, and walking on a slope terrain. In this paper, we focus on the robot's capability of playing soccer. The robot uses a color CCD camera attached on its head as a sensor for playing soccer. To make the robot play soccer with only one camera, an algorithm, which consists of searching, localization, and motion planning, is proposed and experimented. The results show that the robot can play soccer successfully in the given environments.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.720-723
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• 1997

This paper presents a cooperative control method for multiple robots. This method is based on local sensors. The proposed method integrates all information obtained by local perception through a set of sensors and generates commands without logical conflicts in designing control logic. To control multiple robots effectively, a global control strategy is proposed. These methods are constructed by using AND/OR logic and transition firing sequences in Petri nets. To evaluate these methods, the object-searching task is introduced. This task is to search an object like a box by two robots and consists of two sub-tasks, i.e., a wall tracking task and a robot tracking task. Simulation results for the object-searching task and the wall tracking task are presented to show the effectiveness of the method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.629-634
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• 1995

The purpose of this paper is to develop a method of Collision-Free Path Planning (CFPP) for an articulated robot. First, the configuration of the robot is formed by a set of robot joint angles derived fromm robot inverse kinematics. The joint space that is made of the joint angle set, forms a Configuration space (Cspace). Obstacles in the robot workcell are also transformed and mapped into the Cspace, which makes Cobstacles in the Cspace. (The Cobstacles represented in the Cspace is actually the configurations of the robot causing collision.) Secondly, a connected graph, a kind of roadmap, is constructed from the free configurations in the 3 dimensional Cspace, where the configurations are randomly sampled form the free Cspace. Thirdly, robot paths are optimally in order to minimize of the sum of joint angle movements. A path searching algorithm based on A is employed in determining the paths. Finally, the whole procedures for the CFPP method are illustrated with a 3 axis articulated robot. The main characteristics of the method are; 1) it deals with CFPP for an articulated robot in a 3-dimensional workcell, 2) it guarantees finding a collision free path, if such a path exists, 3) it provides distance optimization in terms of joint angle movements. The whole procedures are implemented by C on an IBM compatible 486 PC. GL (Graphic Library) on an IRIS CAD workstation is utilized to produce fine graphic outputs.