The development of unmanned agricultural tractors (UAT) represents a significant step towards intelligent agricultural equipment. UAT technology is expected to lighten the workload of laborers and enhance the accuracy and efficiency of mechanized operations. Through the investigation of 123 relevant studies in the literature published in recent years, this article reviews three aspects of autonomous navigation technologies for UATs: perception, path planning and tracking, and motion control. The advantages and deficiencies of these technologies in the context of UATs are clarified by analyzing technical principles and the status of current research. We conduct summaries and analyses of existing unmanned navigation solutions for different application scenarios in order to identify current bottleneck issues. Based on the analysis of the applicability of autonomous navigation technologies in UATs, it can be seen that fruitful research progress has been achieved. The review also summarizes the common problems seen in current UAT technologies. The application of research to the sharing and integrating of multi-source data for autonomous navigation has so far been relatively weak. There is an urgent need for high-precision and high-stability sensing equipment. The universality of path planning methods and the efficiency and precision of path tracking need to be improved, and it is also necessary to develop highly reliable electrical control modules to enhance motion control performance. Overall, advanced sensors, high-performance intelligent algorithms, and reliable electrical control hardware are key factors in promoting the development of UAT technology.

This study focuses on a wheeled mobile robot used for detection, weeding and information monitoring in agriculture. However, it is difficult to reach satisfactory motion mode switching (MMS) performance. This paper aimed at exploring the optimal control parameters guaranteeing smooth MMS of four-wheel steering. Single factor tests were first conducted using a test-bench. A binary quadratic general rotation combination test was designed to obtain the optimal parameters. An entropy weight method was introduced to construct the four indexes as a comprehensive index. The optimal combination of the parameters was obtained, based on the regression equation. The results showed that the two factors and their interaction had a significant impact on the comprehensive index (p < 0.05). The best combinations of the speed of the stepper motor and locking voltage were 56 r·min⁻¹ and 3.96 V for 15° steering, 72 r·min⁻¹ and 4.35 V for 30°, and 107 r·min⁻¹ and 5.50 V for 45°, respectively. A verification test was performed using the prototype of the robot chassis. The results demonstrated that the MMS process was smooth and stable, and the proposed method was effective. This study is a beneficial exploration of the experimental method concerning wheeled robots.

This paper focuses on the steering motion control of an in-wheel motor-drive robot. The influence of the pulse-width modulation (PWM) duty cycle on steering motion and the steering control method have not yet been proved. Thus, this study aimed to design a steering controller for the off-center steer-by-wire system of a robot. The influence of the PWM duty cycle on the steering motion under different conditions is firstly tested on a test bench. Based on the optimal duty cycles of different cases found in the test, a two-stage fuzzy controller of the duty cycle is designed for the steering system. The first stage of the controller is used to dynamically adjust the PWM duty cycle of the electromagnetic friction lock (EFL). The second stage is designed to realize the self-tuning of the fuzzy controller’s quantization factor and the scale factor. Through two-stage control, the motion of the in-wheel motor and the EFL can be coordinated to realize stable and rapid steering. Considering the robots’ primary application in field roads at present, road tests were ultimately conducted to verify the proposed method. The test results show that the angle response rate of the steering arm is elevated with the increase in the steering angle signal. The proposed controller can sensitively track the target angles with smaller overshoot, yaw rate and lateral acceleration, and better steering accuracy than the PID (proportional–integral–differential) controller under different working conditions.