Improved Pure Pursuit Agricultural Machinery Navigation Curve Path Tracking Method Based on B-spline Optimization

ZHANG Wenyu, HU Liwen WANG, Hui, ZHANG Guocheng, LUO Xiwen, ZHANG Zhigang

Abstract

Aiming at the influence of the smoothness of the sampling path of driving agricultural machinery on the tracking effect and the low tracking adaptability caused by the variable curvature of the curve path, a fuzzy pure tracking control method with integral compensation based on B-spline path optimization was proposed. Firstly, B-spline interpolation method was used to smooth and optimize the sampling path information. Based on the driving law, the interaction between the curvature of agricultural machinery and the operating speed on the tracking control was analyzed, and the pure tracking control method of fuzzy adjusting the forward-looking distance was designed. According to the previous test results, the pure tracking forward looking distance was fuzzy adjusted by the tractor speed and the average curvature of the forward-looking path. At the same time, the tracking lateral deviation was used to design the front wheel angle integral compensation to reduce the steady state error. The Simulink simulation model of curve tracking was designed and constructed, and the simulation experiment was carried out. The simulation results showed that the average absolute and maximum absolute lateral deviation of the improved method were reduced by 4.8% and 7.1% compared with that of the traditional pure tracking control method. The sinusoidal curve tracking test of agricultural machinery in the field was carried out. The interpolation path comparison test results showed that the tracking error after path interpolation was reduced by 75.9% compared with that before interpolation. The control algorithm comparison test results showed that when the agricultural machinery tracked the sinusoidal path with different amplitudes at speeds of 1.0 m/s, 1.5 m/s and 2.5 m/s, the average absolute transverse deviation of the improved pure tracking method was reduced by 36.80%, 62.50% and 61.03%, and the average standard deviation was reduced by 27.8%, 24.0% and 46.3%, respectively. Finally, the random sampling path in the field was tracked. When the speed was 2.5 m/s, the horizontal deviation standard deviation was 0.06 m. This method effectively improved the accuracy of agricultural machinery curve path tracking, and met the agricultural production needs of curve operation.

 

Keywords:agricultural machinery navigation curves, B-spline curve, improve pure pursuit, fuzzy control, integral compensation

 

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