Adhesion Coefficient Identification of Wheeled Mobile Robot under Unstructured Pavement

Author:

Zhang Hongchao12,Song Bao1,Xu Junming1,Li Hu34,Li Shuhui2

Affiliation:

1. School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

2. North China Vehicle Research Institute, Beijing 100072, China

3. Guangdong Intelligent Robotics Institute, Dongguan 523830, China

4. Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China

Abstract

Because of its uneven and large slope, unstructured pavement presents a great challenge to obtaining the adhesion coefficient of pavement. An estimation method of the peak adhesion coefficient of unstructured pavement on the basis of the extended Kalman filter is proposed in this paper. The identification accuracy of road adhesion coefficients under unstructured pavement is improved by introducing the equivalent suspension model to optimize the calculation of vertical wheel load and modifying vehicle acceleration combined with vehicle posture data. Finally, the multi-condition simulation experiments with Carsim are conducted, the estimation accuracy of the adhesion coefficient is at least improved by 3.6%, and then the precision and effectiveness of the designed algorithm in the article are verified.

Funder

National Key R&D Program of China

Guangdong Basic and Applied Basic Research Foundation

Open project of Hubei Key Laboratory of Intelligent Robot

Publisher

MDPI AG

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