• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1999년도 동계 학술대회 논문집
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• pp.122-129
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• 1999

• 한국자동차공학회논문집
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• 제8권5호
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• pp.188-195
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• 2000

This study was conducted to develop the mathematical model and the computer simulation program(TPPMWV) for predicting the tractive performance of off-road wheeled vehicles operated on various soil conditions. The model takes into account main design parameters of a wheeled vehicle, including the radius and width of front and rear tires, the weight of vehicle, wheelbase and driving type(4WD, 2WD). Soil characteristics, such as the peressure-sinkage and shearing characteristics and the response to repetitive loading, are also taken into consideration. The effectiveness of the developed model was verified by comparing the predicted drawbar pulls using TPPMWV with measured ones obtained by field tests for two different driving types of wheeled vehicle. As a results, the drawbar pulls predicted by the TPPMWV were well matched to the measured ones within the absolute errors of 5.25%(4WD) AND 9.42%(2WD)for two different driving types, respectively.

• Journal of Biosystems Engineering
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• 제25권5호
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• pp.359-368
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• 2000

In this paper, mathematical model was developed for predicting the tractive performance of off-road wheeled vehicles operated on soft terrains. Based on the mathematical model, a computer simulation program(TPPMWV) was developed. The model takes into account main design parameters of wheeled vehicle, including radius and width of front and rear tire, weight of vehicle, wheelbase and driving type(4WD, 2WD). Soil characteristics, such as the peressure-sinkage and shearing characteristics and the response to repetitive loading and slip-sinkage effect, are also taken into consideration. The effectiveness of the developed model was verified by comparing the predicted drawbar pulls using TPPMWV with measured ones obtained by field tests for two different driving types of wheeled vehicle. As a results, the drawbar pulls predicted by the TPPMWV were well matched to the measured ones within the absolute errors of 3.916%(4WD) and 13.31%(2WD) for two different driving types, respectively.

• 대한기계학회논문집A
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• 제33권3호
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• pp.251-260
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• 2009

Hybrid locomotive UGV with actively articulated legs along with wheeled ends has high traversability to travel over rough terrain. The behavior control method was usually adapted for the controlling of the suspension configuration which determines the traversability of the UGV. In this study, we are proposing a method of configuration planning of the legs without any detail geometric data about the terrain. The terrain was estimated by the traces of each wheel and the leg configurations for the desired posture of the vehicle were set up against the constraints of the terrain. Also, an optimal leg configuration was calculated based on the quasi-static stability and power consumption, and plans for the leg behavior were made. Validity of the proposed method was checked by simulations using some off-the-shelf programs, and showed that the orientation control without geometric features of terrains and simplification of the behavior planning for obstacle negotiation were possible.

• 대한기계학회논문집A
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• 제33권8호
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• pp.832-841
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• 2009

Wheels of UGV can be used to get the information about the ground. However, wheels of UGV with actively articulated suspension cannot be used as the roles because the each wheel does not remain in contact with the ground. Therefore, in this study, we proposed the indexes and models to estimate the contact wheels. First, we formulated the dynamic equations about the actively articulated suspensions and wheels. Then estimation index $I_{WTC}$ and $I_{ATC}$ were developed from the equations, and analyzed the strengths and weaknesses of each index. As the results, we developed the fuzzy rule-based estimation model additionally derived from our observations. $I_{WTC}$ model and $I_{ATC}$ model could eliminate the noise of about 60% in comparison with the result without the estimation model. Fuzzy model also could reduce the noise of about 83%. In addition, fuzzy rule-based estimation model had high sensitivity and precision as well as robustness.