Aiming at the need to prevent agricultural machinery from colliding with obstacles in the operation of unmanned agricultural machinery, an obstacle detection algorithm using 2D lidar was proposed, and a pre-collision system was designed using this algorithm, which was tested on a harvester. The method uses the differences between lidar data frames to calculate the collision times between the farm machinery and the obstacles. The algorithm consists of the following steps: pre-processing to determine the region of interest, median filtering, and DBSCAN (density-based spatial clustering of applications with noise) to identify the obstacle and calculate of the collision time according to the 6σ principle. Based on this algorithm, a pre-collision system was developed and integrated with agricultural machinery navigation software. The harvester was refitted electronically, and the system was tested on a harvester. The results showed that the system had an average accuracy rate of 96.67% and an average recall rate of 97.14% for being able to stop safely for obstacles in the area of interest, with a summed average of 97% for both the accuracy and recall rates. The system can be used for an emergency stop when encountering obstacles in the automatic driving of agricultural machinery and provides a basis for the unmanned driving of agricultural machinery in more complex scenarios.
This article analyzed the shortcomings of the present laser land leveling machine, when it works on the uneven land. A self-balancing adjustment control system is proposed, which attempt to expand the implement level control, so as to improve and enhance the leveling precision and efficiency. This system can automatically keep the agricultural implements balance when it works in the uneven land. Real-time roll angle of the implement was obtained be a gyroscope sensor, which fixed on the center of the implement. The controller actuate the magnetic valve according to the real-time roll angle of the implement. This study provides a method for auto leveling controlling system of agricultural implement. which can improve the flatness of the land. With this control system, the absolute roll angle of the implement, which worked on a 15 °slope land has decreased 47.8%, the relative improvement is 18.6%, and the land altitude intercept is less than 1%.
The performance of automatic steering control directly affects the accuracy of tractor navigation. In order to improve the tractor navigation performance, the tractor automatic steering control technology is researched. The automatic steering control system for the full hydraulic steering tractor is designed with the Lovol Europard FT704 tractor. The mathematical model of automatic steering system is established. The PID parameters are determined by digital simulation analysis, and verified by steering test. The field test results show that the offset error is not greater than 5.98 cm and the average offset error is not greater than 1.23 cm at the travel speed of 1.0 m/s. The field tests indicated the tractor automatic steering control system can meet the needs of tractor automatic navigation.
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