The precision of curve path tracking affects the efficiency of unmanned rice transplanter by affecting the efficiency of line changing. In order to improve the curve path tracking accuracy of the unmanned rice transplanter when turning from the headland, in view of the poor adaptability of the traditional linear quadratic regulator (LQR) path tracking controller with fixed error weight matrix to the changes of the longitudinal speed, lateral deviation and heading angle deviation of the rice transplanter, an optimization method of path tracking controller by adjusting the error weight matrix of linear quadratic regulator in real time through fuzzy control was presented. The method took the longitudinal speed, lateral deviation and heading angle deviation as the input, and the error weight corresponding to the lateral deviation and heading angle deviation as the output, and a fuzzy control model was established to adjust the error weight matrix of the linear quadratic regulator in real time. In order to verify the accuracy and feasibility of the curve path tracking control of the proposed algorithm, the refitted Yangma VP6E unmanned rice transplanter was taken as the object, and Carsim and Simulink joint simulation tests and real vehicle tests were carried out. The simulation test results showed that when the rice transplanter was controlled to track a quarter arc path with radius of 2m, the average value of absolute value of lateral deviation under the control of the proposed algorithm was 0.014m, the maximum value was 0.032m, and 100% of those were less than 0.04m, the average value of the absolute value of heading angle deviation was 1.67°, and the maximum value was 4.94°. Compared with the traditional linear quadratic regulator with feedforward control, the average value of absolute value of lateral deviation was reduced by 50%, the average absolute value of heading angle deviation was decreased by 23%. The real vehicle test results showed that when the rice transplanter tracked a quarter arc path with radius of 2m, the average value of the absolute value of lateral deviation under control of proposed algorithm was 0.027m, the maximum value was 0.048m, and 62% of those were less than 0.04m, the average value of absolute value of heading angle deviation was 1.86°, and the maximum value was 4.94°. Compared with the traditional linear quadratic regulator with feedforward control, the average value of absolute value of lateral deviation was reduced by 40%. The average absolute value of heading angle deviation was decreased by 4.1%. The method improved the curve path tracking control accuracy of the unmanned rice transplanter, and provided a reference for the curve path tracking control of the unmanned rice transplanter.