• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.395-396
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• 2007

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.327-334
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• 2011

It is necessary that UGV(Unmanned Ground Vehicle) should generate a real-time travesability index map by analyzing raw terrain information to travel autonomously tough terrain which has various slope and roughness values. In this paper, we propose a local path planning method, $MA^*$(Modified $A^*$) algorithm, using DVGM (Directional Velocity Grid Map) for unmanned ground vehicle. We also present a path optimization algorithm and a path smoothing algorithm which regenerate a pre-planned local path by $MA^*$ algorithm into the reasonable local path considering the mobility of UGV. Field test is conducted with UGV in order to verify the performance of local path planning method using DVGM. The local path planned by $MA^*$ is compared with the result of $A^*$ to verify the safety and optimality of proposed algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.3
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• pp.1-9
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• 2007

A major concern for Autonomous Military Robot in the rough terrain is the problem of moving robot from an initial configuration to goal configuration. In this paper, We generate a local path to looking for the best route to move an goal configuration while avoiding known obstacle from world model, not violating the mobility constraints of robot. Trough a Simulator for Unmanned Autonomous Vehicle, We can simulate a traversability of unmanned autonomous vehicle based on steering, acceleration, braking command obtained from local path planning.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.359-370
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• 2007

Lane tracking and obstacle avoidance are considered two of the key technologies on an unmanned ground vehicle system. In this paper, we propose a method of lane tracking and obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. First, obstacle avoidance consists of two parts: a longitudinal control system for acceleration and deceleration and a lateral control system for steering control. Each system is used for unmanned ground vehicle control, which notes the vehicle's location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacle and perform obstacle avoidance on the road, which involves vehicle velocity. Second, we explain a method of lane tracking by means of a vision system, which consists of two parts: First, vehicle control is included in the road model through lateral and longitudinal control. Second, the image processing method deals with the lane tracking method, the image processing algorithm, and the filtering method. Finally, in this paper, we propose a method for vehicle control, modeling, lane tracking, and obstacle avoidance, which are confirmed through vehicles tests.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.451-459
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• 2011

Fundamentally, there are 5 systems are needed for autonomous navigation of unmanned ground vehicle: Localization, environment perception, path planning, motion planning and vehicle control. Path planning and motion planning are accomplished based on result of the environment perception process. Thus, high reliability of localization and the environment perception will be a criterion that makes a judgment overall autonomous navigation. In this paper, via map matching using vehicle dynamic model and LIDAR sensors, replace high price localization system to new one, and have researched an algorithm that lead to robust autonomous navigation. Finally, all results are verified via actual unmanned ground vehicle tests.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.127-133
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• 2004

This paper described development of the portable ground control system(PGCS) for unmanned aerial vehicle. In the design of GCS, it upload mission planning that aircraft has to perform and has to receive position, attitude, state, navigation information all about the aircraft. Aircraft states and trajectory are displayed using this system on line. The PGCS is composed of commercial notebook computer, RF modem for communication between aircraft and PGCS, input/output board, remote control receiver, switches and lamps. Performance of this system is verified by flight test of small unmanned aerial vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1246-1253
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• 2009

To be high efficient for a navigation of unmanned ground vehicle, it must be able to distinguish between safe and hazardous regions in its immediate environment. We present an advanced method using laser range finder for building global 2D digital maps that include environment information. Laser range finder is used for mapping of obstacles and driving environment in the 2D laser plane. Rotary encoders are used for localization of UGV. The main contributions of this research are the development of an algorithm for global 2D map building and it will turn a UGV navigation based on map matching into a possibility. In this paper, a map building algorithm will be introduced and an assessment of algorithm reliability is judged at an each environment.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.549-556
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• 2009

One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.313-318
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• 2010

The power plant system of a tilt rotor unmanned aerial vehicle (UAV) was verified by the Ironbird ground test, which considerably reduces cost and risk during the developmental stages. The function and performance of the engine, drive line, nacelle conversion, and rotor systems were evaluated using a building block test approach. The Ironbird test concept facilitates the discovery of potential faults in earlier stages of the testing period. As a result, the developmental testing period could effectively be shortened. The measured test data acquired through a ground control and data acquisition system exhibited satisfactory results which meet the developmental specifications of a tilt rotor UAV.