• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.107-115
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• 2008

Accurate extraction of traversable region is a critical issue for autonomous navigation of unmanned ground vehicle(UGV). This paper introduces enhanced extraction of traversable region by combining scene clustering with 3D world modeling using CCD(Charge-Coupled Device)/IR(Infra Red) image. Scene clustering is developed with K-means algorithm based on CCD and IR image. 3D world modeling is developed by fusing CCD and IR stereo image. Enhanced extraction of traversable regions is obtained by combining feature of extraction with a clustering method and a geometric characteristic of terrain derived by 3D world modeling.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.719-725
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• 2013

In this paper, we propose a local path planning method based on RANGER algorithm and autonomy manager for autonomous navigation of UGV in urban environment. LPP method is designed to generate the local path in sensing area by using lane and curb of pavement and autonomy manager is designed to make a decision which transit the status of LPP component to a proper status for current navigation environment. A field test is conducted with scenarios in real urban environment in which crossroad, crosswalk and pavement are included and the performance of proposed method is validated.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.726-732
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• 2013

It is required for UGV(Unmanned Ground Vehicle) to have a LPP(Local Path Plan) component which generate a local path via the center of road by analyzing binary map to travel autonomously unpaved road in rough environment. In this paper, we present the method of boundary estimation for unpaved road and a local path planning method based on RANGER algorithm using the estimated boundary. In specially, the paper presents an approach to estimate road boundary and the selection method of candidate path to minimize the problem of zigzag driving based on Bayesian probability reasoning. Field test is conducted with scenarios in rough environment in which bush, tree and unpaved road are included and the performance of proposed method is validated.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.114-122
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• 2011

We propose an automatic localization technique based on Uniform Arc Length Sampling (UALS) of 360 degree range sensor data. The proposed method samples 3D points from dense a point-cloud which is acquired by the sensor, registers the sampled points to a digital surface model(DSM) in real-time, and determines the location of an Unmanned Ground Vehicle(UGV). To reduce the sampling and registration time of a sequence of dense range data, 3D range points are sampled uniformly in terms of ground sample distance. Using the proposed method, we can reduce the number of 3D points while maintaining their uniformity over range data. We compare the registration speed and accuracy of the proposed method with a conventional sample method. Through several experiments by changing the number of sampling points, we analyze the speed and accuracy of the proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1285-1294
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• 2010

This study describes the design and verification of short range UWB(Ultra Wideband) imaging radar that is able to display high resolution radar image for front area of a UGV(Unmanned Ground Vehicle). This radar can help a UGV to navigate autonomously as it detects and avoids obstacles through foliage. We describe the relationship between bandwidth of transmitting signal and range resolution. A vivaldi antenna is designed and it's radiation pattern and reflection are measured. It is easy to make array antenna because of small size and thin shape. Aperture size of receiving array antenna is determined by azimuth resolution of radar image. The relation of interval of receiving antenna array, image resolution and aliasing of target on a radar image is analyzed. A vector network analyzer is used to obtain the reflected signal and corner reflectors as targets are positioned at grass field. Applicability of the proposed radar to UGV is proved by analysis of image resolution and penetrating capability for grass in the experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.369-370
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• 2011

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.4
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• pp.340-346
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• 2008

An unmanned surveillance robot consists of a machine gun, a laser receiver, a thermal imager, a color CCD camera, and a laser illuminator. It has two axis control systems for elevation and azimuth. Because the current robot system is mounded at a fixed post to take care of surveillance tasks, it is necessary to modify such a surveillance robot to be installed on an UGV (Unmanned Ground Vehicle) system in order to watch blind areas. Thus, it is required to have a stabilization system to compensate the disturbance from the UGV. In this paper, a simulation based design scheme has been adopted to develop a mobile surveillance robot. The 3D CAD geometry model has first been produced by using Pro-Engineer. The required pan and tilt motor capacities have been analyzed using ADAMS inverse dynamics analysis. A target tracking and stabilization control algorithm of the mobile surveillance robot has been developed in order to compensate the motion of the vehicle which will experience the rough terrain. To test the performance of the stabilization control system of the robot, ADAMS/simulink co-simulations has been carried out.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.138-142
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• 2014

This research presents an A* based algorithm which can be applied to Unmanned Ground Vehicle self-navigation in order to make the driving path smoother. Based on the grid map, A* algorithm generated the path by using straight lines. However, in this situation, the knee points, which are the connection points when vehicle changed orientation, are created. These points make Unmanned Ground Vehicle continuous navigation unsuitable. Therefore, in this paper, B-spline curve function is applied to transform the path transfer into curve type. And because the location of the control point has influenced the B-spline curve, the optimal control selection algorithm is proposed. Also, the optimal path tracking speed can be calculated through the curvature radius of the B-spline curve. Finally, based on this algorithm, a path created program is applied to the path results of the A* algorithm and this B-spline curve algorithm. After that, the final path results are compared through the simulation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.55-59
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• 2008

For effective mobility control of UGV(unmanned ground vehicle), the terrain cover classification is an important component as well as terrain geometry recognition and obstacle detection. The vision based terrain cover classification algorithm consists of pre-processing, feature extraction, classification and post-processing. In this paper, we present a method to classify terrain covers based on the color and texture information. The color space conversion is performed for the pre-processing, the wavelet transform is applied for feature extraction, and the SVM(support vector machine) is applied for the classifier. Experimental results show that the proposed algorithm has a promising classification performance.

• Journal of Applied Reliability
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• v.15 no.2
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• pp.131-138
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• 2015

In modern warfare, the number of unmanned systems grow faster than any other weapon systems. Therefore, it is very important to predict and measure the combat effectiveness (CE) of unmanned weapon systems in battlefield for deciding defense budget to acquire those systems. In general, quantitative calculation of weapon effectiveness under complicated battlefield is difficult based on the future network centric warfare. Hence, many papers studied how to measure the combat effectiveness and tried to study a lot of related issues about it. However, there are few papers dealing with the relationship between the UGV (Unmanned Ground Vehicle)'s performance and CE in a ground battlefield. In this paper, we do the sensitivity analysis based on a given scenario in a small unit battle. In order to do that, we developed simulation model using AnyLogic and changed the input parameters such as detection and hitting probabilities. We also assess the simulation outputs according to the variation of input parameters. The MOE used in this simulation model output is survival ratio for Blue force. We hope that this paper will be useful to find which input variable is more effective to increase combat effectiveness in a small unit ground battlefield.