Development of a Path Generation and Tracking Algorithm for a Korean Auto-guidance Tillage Tractor (original) (raw)
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Path planning for autonomous lawn mower tractor
Path planning is an essential part for traveling and mowing of autonomous lawn mower tractors. Objectives of the paper were to analyze operation patterns by a skilled farmer, to extract and optimize waypoints, and to demonstrate generation of formatted planned path for autonomous lawn mower tractors. A 27-HP mower tractor was operated by a skilled farmer on grass fields. To measure tractor travel and operation characteristics, an RTK-GPS antenna with a 6-cm RMS error, an inertia motion sensing unit, a gyro compass, a wheel angle sensor, and a mower on/off sensor were mounted on the mower tractor, and all the data were collected at a 10-Hz rate. All the sensor data were transferred through a software program to show the status immediately on the notebook. Planned path was generated using the program parameter settings, mileage and time calculations, and the travel path was plotted using developed software. Based on the human operation patterns, path planning algorithm was suggested for autonomous mower tractor. Finally path generation was demonstrated in a formatted file and graphic display. After optimizing the path planning, a decrease in distance about 13% and saving of the working time about 30% was achieved. Field test data showed some overlap, especially in the turning areas. Results of the study would be useful to implement an autonomous mower tractor, but further research needs to improve the performance.
This paper describes a robust procedure to obtain a guidance directrix for agricultural tractors in plowing operation with the wide toolbar. The automatic steering algorithm controls the vehicles based on the position of the trajectory results of previous operation on the field. Hough transform method was adapted to process forward view images of a vehicle captured by a digital camera installed at 1.1m height and angle of 35o respect to line of travel. The contrast between disturbed soil and undisturbed soil was the basis for detection of the last track of the machine. This algorithm was tested in the various situations including various illumination conditions and various plant residues. The position of the detected line respect to the furrow was measured by algorithm. The methodology devised to overcome the image noise problems and to be able to determine the proper trajectory for the tractor. The algorithm was able to find the trajectory with high accuracy. Maximum deviation of the detected line from the desired trajectory was measured up to 1.72cm. The suggested algorithm is able to assist the operator during manual guidance of wide plowing tools.
Development of a Guidance System for an Agricultural Wheeled Robotic Platform in Row Crop Fields
Biomechanism and Bioenergy Research, 2024
Smart and precision agriculture seeks to boost the efficiency of operations and crop yield by using modern technology. Modern tools such as sensors, imagery cameras, and deep learning enable farmers to identify and control weeds, pests, and diseases in real-time. A robotic platform can carry these modern types of equipment and achieve the mentioned objectives precisely. Automatic and accurate navigation of this autonomous robot in agricultural fields is essential for performing these precision tasks. An agricultural robotic platform was designed and developed for row crop fields. The robot navigation system comprises two main components: a vision-based row detection system for path tracking and a motion controller system. The vision-based guidance system processes acquired image data from a tilted camera in front of the robot to identify the crop row's position. The Hough transform method was used to determine the position of the crop rows. Using the resultant guidance line equations, the motion controller directs the robot to move automatically between rows without harming the crops. Differential speed steering allows both wheels on the robot to rotate at different speeds. The steering system improved the robot position error by controlling both powered wheel speeds. To move the robot among the crop rows, it generates the wheel speed difference command. The robotic platform effectively followed the rows of sugar beets at a velocity of 0.5 m/s, exhibiting an average lateral offset of 12 mm and a standard deviation of 22 mm.
The main objective of this study was to develop a guidance-assistance system for agricultural vehicles in land preparation and tilling operations. The proposed system is a potential replacement for markers on the implement toolbar. The new automatic steering system controls the vehicle path based on the trace of the previous tilling operation on the field. Hough transform method was adapted to process forward view images of the tractor captured by a digital camera. For traces coinciding with center line of the images no correction is necessary, otherwise the relative position of the trace with respect to image center line would be an indication of the need for steering wheel adjustment. The proposed system was evaluated at various conditions including three illumination levels, previous plant residue levels (9, 24 and 50%) and soil surfaces tilled by one of the three implements (plow, subsoiler and row-crop plant furrow opener). For each test accuracy of algorithm was determined and Line Prediction Error (LPE) was calculated by the algorithm. Tests were conducted in field at three forward speeds; 4, 7.5 and 11 km h -1 and three steering angles; 10 o , 16 o and 20.5 o . Distance error (DE) and response time (RT) for each forward speed and steering angle was measured and compared. Results indicated that various illumination and residue levels have not distorted the output of the system proposed (LPE was limited to ±1.72 cm). Response time was decreased for increasing forward speed and steering angle. Effect of forward speed on DE was significant whereas effect of steering angle on DE was not significant (0.05p).
Navigational Path-Planning For All-Terrain Autonomous Agricultural Robot
ArXiv, 2021
The shortage of workforce and increasing cost of maintenance has forced many farm industrialists to shift towards automated and mechanized approach. The key component for autonomous systems is the path planning techniques used. Coverage path planning (CPP) algorithm is used for navigating over farmlands to perform various agricultural operations such as seeding, ploughing, or spraying pesticides and fertilizers. This report paper compares novel algorithms for autonomous navigation of farmlands. For reduction of navigational constraints, a high-resolution grid map representation is taken into consideration specific to Indian environments. The free space is covered by distinguishing the grid cells as covered, unexplored, partially explored and presence of obstacle. The performance of the compared algorithms is evaluated with metrics such as time efficiency, space efficiency, accuracy, and robustness to changes in the environment. Robotic Operating System (ROS), Dassault Systemes Exper...
Review of control on agricultural robot tractors
2020
This article studies the most common methods of autonomous vehicle guidance, as well as a review of companies that have already developed their own self-guided tractors. The most common methods for autonomous guidance are through the position obtained from an RTK-GPS and by artificial vision. For both cases, sensors have to be implemented that help the task assigned, such as LIDAR sensors, proximity sensors, among others, that detect the tractor to know the working environment and define the correct route and even avoid collision, to comply with the assigned task, managing to improve production time and quality. The two guidance methods mentioned in this work fail to have error = 0, either by the type of sensor or by the technique used. Among the most commonly used techniques for obstacle avoidance are the possible field method or the probabilistic route planner.
Review of research on agricultural vehicle autonomous guidance
2009
A brief review of research in agricultural vehicle guidance technologies is presented. The authors propose the conceptual framework of an agricultural vehicle autonomous guidance system, and then analyze its device characteristics. This paper introduces navigation sensors, computational methods, navigation planners and steering controllers. Sensors include global positioning systems (GPS), machine vision, dead-reckoning sensors, laser-based sensors, inertial sensors and geomagnetic direction sensors. Computational methods for sensor information are used to extract features and fuse data. Planners generate movement information to supply control algorithms. Actuators transform guidance information into changes in position and direction. A number of prototype guidance systems have been developed but have not yet proceeded to commercialization. GPS and machine vision fused together or one fused with another auxiliary technology is becoming the trend development for agricultural vehicle ...
DESIGN OF AUTOMATIC NAVIGATION CONTROL SYSTEM FOR AGRICULTURAL VEHICLE
The tractor automatic navigation technology is one of the hottest research fields of precision agriculture as well as a major means for realizing intelligent operating of agricultural vehicle in future. This paper presents a thorough research on GPS automatic navigation technology of agricultural vehicle considering that working conditions and field conditions for the tractor are complex and that there is a high requirement on the precision of the driving path of the tractor. Major contents of the research are as follows: The hydraulic control valve was selected by testing. A hydraulic control valve test platform specific to navigation was designed. The test platform can gather information about the flow and pressure of each measured hydraulic valve in a real-time manner. A navigation valve block was developed. Finally, the navigation valve block was used in electro-hydraulic transformation of model vehicle, realizing the control of electrical signal in tractor steering. A hardware platform for the automatic navigation system was built. A navigation controller based on ARM chip, the RTK-GPS positioning system and the angle sensor constitute the hardware platform of the autopilot system of the tractor. The hardware platform is the basis for realizing automatic navigation of the tractor. The navigation control algorithm was studied, pure pursuit model tracking algorithm were analyzed; the navigation decision-making control system based on the pure pursuit model tracking algorithm was designed; the kinematics model of the tractor was established. The pure tracking model has been simulated by MATLAB software, and the system has good stability and sensitivity. The experimental research on the automatic navigation system of the tractor was conducted. Based on the automatic navigation platform developed above, experiments on the control of the tractor walking straight at the flat road have been done. The results proved that the automatic navigation system has the capability of tracking the straight path of the tractor in a real-time and stable manner and meets the requirements of precision agriculture.
Autonomous Agricultural Tractor with an Intelligent Navigation System
IFAC Proceedings Volumes, 2001
This paper reports the development of an autonomous agricultural tractor with an intelligent navigation system. The intelligent navigation system consisted of a set of redundant guidance sensors, a sensor fusion algorithm, and an intelligent navigation algorithm. This autonomous tractor was built on a Case-IH Magnum I' MX-240 2-wheel drive agricultural tractor platform. Evaluation tests on autonomous planting and row crop cultivating verified that this autonomous tractor could autonomously perform planting and cultivating functions on typical Midwest farming land. It could achieve an operating speed of 8 m/s ith a small trajectory tracking error of less than 0.05m.
Development of a flexible platform for agricultural automatic guidance research
ASAE paper, 1998
This paper describes an agricultural vehicle modified to serve as a research platform for agricultural engineering. A tractor was equipped with a global positioning receiver, inertial/GPS system, geomagnetic direction sensor, and a monochrome camera for local and global sensing. For steering control, the tractor was equipped with an electro-hydraulic proportional steering valve, PWM coil valve driver, and potentiometer wheel angle sensor. The high flexibility of this platform has enabled research in the areas of row crop guidance, sensor fusion and evaluation, automation, vehicle dynamics modeling, and steering control. We discuss the benefits and drawbacks to this platform and the research made available through its development.