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Predicting Maximum Traction to Improve Maneuverability for Autonomous Mobile Robots on Rough Terrain

Jayoung Kim and Jihong Lee
Mechatronics Group at Chungnam National University, Daejeon, Republic of Korea

Abstract—This paper proposes a method to predict maximum traction force for autonomous mobile robots on rough terrain in order to improve maneuverability. For predicting traction force, we utilize friction-slip curves based on modified Brixius model derived empirically in terramechanics, which is a function of mobility number Bn′ and slip ratio S. Friction-slip curves include physical characteristics of various rough terrains such as firm soil, sandy soil and grass-covered soil. Also, we build prediction models for terrain parameters; maximum static friction and optimal slip ratio on friction-slip curves. Mobility number Bn′ is estimated from modified Willoughby Sinkage model which is a function of sinkage z and slip ratio S. Therefore, if sinkage z and slip ratio are measured once by sensors such as a laser sensor and a velocity sensor, then mobility number Bn′ is estimated and maximum traction force is predicted from a prediction model for terrain parameters. Estimation results for terrain parameters are shown in a driving simulation using MATLAB. Prediction performances for maximum traction of various terrains are evaluated as high accuracy through analysis of estimation errors. 

Index Terms—autonomous mobile Robot, brixius terrain Model, maneuverability, maximum traction, friction coefficient, rough terrain.
 
Cite: Jayoung Kim and Jihong Lee , "Predicting Maximum Traction to Improve Maneuverability for Autonomous Mobile Robots on Rough Terrain ," Journal of Automation and Control Engineering, Vol.1, No.1,   pp. 1-6, March 2013. doi: 10.12720/joace.1.1.1-6 ,  ,

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