• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2435-2437
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• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1132-1135
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• 1996

The objective of this paper is to make a model-based map for the localization of an autonomous mobile robot(AMR) from ultrasonic sensor measurements, that are acquired when the AMR explores unknown indoors. First, the AMR navigates on unknown space by wall-following and gathers range data from the ultrasonic sensor. Then, the range data are converted to a wall-marked gird map, from which lines representing the walls are extracted using the Hough transform. This process is implemented on an AMR having an ultrasonic sensor, and a preliminary experimental result is presented.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.444-450
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• 2011

Environmental change, labor shortage, and international trade politics make agricultural automation ever more important. The automation demands the highest technology due to the nature of agriculture. In this paper, autonomous pesticide spray robot system has been developed for rose farming in the glass house. We developed drive platform, navigation/localization system, atomization spray system, autonomous, remote, and manual operation system, and monitoring system. The robot will be a great contribution to automation of hazardous labor-demanding chore of pesticide control in glass houses.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.149-158
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• 2024

This paper presents a robust autonomous navigation and reconnaissance system for tracked robots, designed to handle complex multi-floor indoor environments with stairs. We introduce a localization algorithm that adjusts scan matching parameters to robustly estimate positions and create maps in environments with scarce features, such as narrow rooms and staircases. Our system also features a path planning algorithm that calculates distance costs from surrounding obstacles, integrated with a specialized PID controller tuned to the robot's differential kinematics for collision-free navigation in confined spaces. The perception module leverages multi-image fusion and camera-LiDAR fusion to accurately detect and map the 3D positions of objects around the robot in real time. Through practical tests in real settings, we have verified that our system performs reliably. Based on this reliability, we expect that our research team's autonomous reconnaissance system will be practically utilized in actual disaster situations and environments that are difficult for humans to access, thereby making a significant contribution.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.81-86
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• 2004

This paper describes self-localization of a mobile robot from the multiple candidates of landmarks in outdoor environment. Our robot uses omnidirectional vision system for efficient self-localization. This vision system acquires the visible information of all direction views. The robot uses feature of landmarks whose size is bigger than that of others in image such as building, sculptures, placard etc. Robot uses vertical edges and those merged regions as the feature. In our previous work, we found the problem that landmark matching is difficult when selected candidates of landmarks belonging to region of repeating the vertical edges in image. To overcome these problems, robot uses the merged region of vertical edges. If interval of vertical edges is short then robot bundles them regarding as the same region. Thus, these features are selected as candidates of landmarks. Therefore, the extracted merged region of vertical edge reduces the ambiguity of landmark matching. Robot compares with the candidates of landmark between previous and current image. Then, robot is able to find the same landmark between image sequences using the proposed feature and method. We achieved the efficient self-localization result using robust landmark matching method through the experiments implemented in our campus.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.168-177
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• 2008

Path finding is a key element in the navigation of a mobile robot. To find a path, robot should know their position exactly, since the position error exposes a robot to many dangerous conditions. It could make a robot move to a wrong direction so that it may have damage by collision by the surrounding obstacles. We propose a method obtaining an accurate robot position. The localization of a mobile robot in its working environment performs by using a vision system and Virtual Reality Modeling Language(VRML). The robot identifies landmarks located in the environment. An image processing and neural network pattern matching techniques have been applied to find location of the robot. After the self-positioning procedure, the 2-D scene of the vision is overlaid onto a VRML scene. This paper describes how to realize the self-positioning, and shows the overlay between the 2-D and VRML scenes. The suggested method defines a robot's path successfully. An experiment using the suggested algorithm apply to a mobile robot has been performed and the result shows a good path tracking.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1597-1600
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• 1997

Most autonomous mobile robots view things only in front of them. As a result they may collide against objects moving from the side or behind. To overcome the problem we have built an Active Omni-directional Range Sensor that can obtain omni-directional depth data by a laser conic plane and a conic mirror. Also we proposed a self-localization algorithm of mobile robot in unknown environment by fusion of Odometer and Active Omn-directional Range Sensor.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.34.2-34
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• 2002

● Introduction ● The environment of the RoboSot ● Extracting landmarks & feature points ● Experimental results ● Conclusion

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.83-85
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• 2005

Exploration involving mapping and localization in an unknown environment is an important task in mobile robots. For this, robot must be able to build a reliable map of surroundings and to estimate the position of it. In this paper, we developed technique for gird-based localization of a mobile robot with ultrasonic sensors using EKF(Extended Kalman Filter). We also describe the information about landmarks detected in the environment. Finally, the robot experiments show the efficiency of our approach in the real environment.