• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.30.4-30
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• 2001

In this paper, design and integration of a newly developed double-tracked mobile robot called ROBHAZ-DT are introduced. It is designed to carry out military and civil missions in various hazardous environments such as the areas of fire, war, disaster and mine field etc. ROBHAZ-DT is configured with three mechanical bodies, namely front, rear and main body. By using its rotational passive adaptation mechanism equipped between the front and rear bodies, ROBHAZ-DT shows a good mobile capability on uneven terrain including stairs. The passive adaptation mechanism reduces energy consumption and offers simplicity in the design of the ROBHAZ-DT ...

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.198-202
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• 2009

Urban Search and Rescue (USAR) involves locating, rescuing (extricating), and medically stabilizing victims trapped in confined spaces. In this paper we state the current approach to USAR, address the limitations and discuss the way for moving in rugged topography. To achieve objectives such as surveillance, reconnaissance, and rescue, it is necessary to develop a driving mechanism that can handle rugged geographical features. We propose a new type of driving mechanism for a rescue robot that has a variable shape single-track. By using a variety shapes, it can get the gain of steering and rotating and the ability to overcome stairs. In this paper, we analyzed the design parameters for making variable transform shapes and determined the specifications of the robot to enhance adaptability to stairs.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.749-757
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• 2001

We present a simple artificial landmark model and robust landmark tracking algorithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a clustered scene robustly. With the tracked single landmark, we extract geometrical information than achieve accurate localization.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.329-334
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• 2011

This paper presents the method for location estimation with obstacle tracking method. A laser scanner is used to implement the system, and we assume that the map information is known. We matches the measurement of the laser scanner to estimate the location of the robot by using sequential monte carlo (SMC) method. After estimating the robot's location, the pose of obstacles are detected and tracked, hence, we can predict the collision risk of them. Finally, we present the experiment results to verify the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.279-285
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• 2016

In this paper, a platform design of caterpillar typed electrical vehicle is proposed. Nowadays, there have been many researches on mobile robots in the various ways. Many different fields such as military, exploration, agricultural assistance and disaster relief have applied the mobile robot. Design condition of stable angle, upset angle is reflect to caterpillar typed electrical vehicle. To experiment, developed a caterpillar typed electrical vehicle and design a driving controller. Developed caterpillar typed electrical vehicle is tested about operating and driving. Test environment is consisted of driving on flatland and climbing 15 degree and outdoor 40 degree slope. It is confirmed that developed tracked electric vehicular robot can driving and climbing.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.29-39
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• 2019

As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.40-47
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• 2010

This paper presents a simultaneous localization and mapping (SLAM) of an indoor hallway environment using Rao-Blackwellized particle filter (RBPF) along with a line segment as a landmark. Based on the fact that fluent line features can be extracted around the ceiling and side walls of hallway using vision sensor, a horizontal line segment is extracted from an edge image using Hough transform and is also tracked continuously by an optical flow method. A successive observation of a line segment gives initial state of the line in 3D space. For data association, registered feature and observed feature are matched in image space through a degree of overlap, an orientation of line, and a distance between two lines. Experiments show that a compact environmental map can be constructed with small number of horizontal line features in real-time.