• 한국CDE학회논문집
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• 제19권4호
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• pp.332-339
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• 2014

This paper presents on the development of wheel-terrain interaction device using low-priced sensors, which will be used to predict the drawbar pull and optimal slip of off-road vehicle in real time. The essential variables obtained in the device to predict the mobility of vehicles are determined based on semi-empirical model describing the wheel-terrain interaction. Using the developed device, the experiments about the wheel-terrain interaction were performed on the soil of the Jumunjin standard sand, which yielded dynamic weight, motor driving torque, drawbar pull, and sinkage with respect to wheel slip ratio. Finally, the repeatability of the measured data are verified through repeating the experiments three times on the same condition.

• 로봇학회논문지
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• 제8권2호
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• pp.116-128
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• 2013

This paper focuses on development of a testbed for analysis of robot-terrain interaction on rough terrain and also, through one wheel driving experiments using this testbed, prediction of maximum velocity and acceleration of UGV. Firstly, from the review regarding previous researches for terrain modeling, the main variables for measurement are determined. A testbed is developed to measure main variables related to robot-terrain interaction. Experiments are performed on three kinds of rough terrains (grass, gravel, and sand) and traction-slip curves are obtained using the data of the drawbar pull and slip ratio. Traction-slip curves are used to predict driving performance of UGV on rough terrain. Maximum velocity and acceleration of UGVs are predicted by the simple kinematics and dynamics model of two kinds of 4-wheel mobile robots. And also, driving efficiency of UGVs is predicted to reduce energy consumption while traversing rough terrains.

• 제어로봇시스템학회논문지
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• 제20권1호
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• pp.58-69
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• 2014

This paper proposes a method for predicting maximum friction coefficients and optimal slip ratios as optimal control parameters for traction control or slip control of autonomous mobile robots on rough terrain. This paper focuses on strength of ground surface which indicates different characteristics depending on material types on surface. Strength of various material types can be estimated by Willoughby sinkage model and by a developed testbed which can measure forces, velocities, and displacements generated by wheel-terrain interaction. Estimated strength is collaborated on building improved Brixius model with friction-slip data from experiments with the testbed over sand and grass material. Improved Brixius model covers widespread material types in outdoor environments on predicting friction-slip characteristics depending on strength of ground surface. Thus, a prediction model for obtaining optimal control parameters is derived by partial differentiation of the improved Brixius model with respect to slip. This prediction model can be applied to autonomous mobile robots and finally gives secure maneuverability on rough terrain. Proposed method is verified by various experiments under similar conditions with the ones for real outdoor robots.