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Development of a Robot Combine Harvester for Wheat and Paddy Harvesting
Development of a Robot Combine Harvester for Wheat and Paddy Harvesting Ze Zhang*. Noboru Noguchi**. Kazunobu Ishii***. Liangliang Yang. Chi Zhang. Graduate School of Agriculture, Hokkaido University, Nishi-9, Kita-9, Kita-ku, Sapporo, Hokkaido, 060-8589, Japan *(e-mail: [email protected]) **(e-mail: [email protected]) ***(e-mail: [email protected])
Abstract: Currently, the number of farmers in Japan is decreasing at an especially high speed. In addition, the average age of the farmers available is increasing. In this trend, it is entirely possible that several decades later, the self-sufficiency rate of agricultural product in Japan will drop sharply. To solve this problem, one possible solution should be to employ agricultural robot in actual use, including robot tractor, robot combine harvester and so on. Recognizing the importance and urgency of developing such agricultural robots, this study proposed and developed a robot combine harvester. This robot relies on an AGI GPS receiver and IMU for position and posture data. It is controlled via CAN BUS. In this study, its accuracy was tested, and it shows that this combine harvester can be applied in Honshu and Hokkaido area of Japan with this accuracy. Keywords: Robot, Combine Harvester, Path-Plan, GPS, IMU 1. INTRODUCTION In Japan, agriculture is confronted with several serious problems, such as the shortage and aging of labor force. To solve these problems, the Ministry of Agriculture, Forestry and Fishery of Japan (MAFF) has launched a plan to promote the development of robots for agricultural use. This also aims at increasing agricultural productivity and improving selfsufficiency in Japan. Currently, many different types of agricultural robots are under development in Japan, such as a robot wheel-type tractor (Kise et al., 2002, Yang et al., 2012), a robot crawlertype tractor (Takai et al., 2010), a robot rice transplant machine (Nagasaka et al., 2004) and a robot combine harvester (Iida et al., 2011). In all the research mentioned above, a real-time kinematic GPS receiver and an IMU/GPS compass are required. Usually, a GPS receiver alone is not sufficient to ensure that a robot vehicle achieve a precise control (Matsui, 2007), consequently, an IMU or a GPS compass is commonly required as a heading sensor. The goal of this research is to develop a combine harvester with different functions that are eligible to practical crop harvesting, such as wheat and/or paddy harvesting. This combine harvester uses an RTK-GPS embedded with an IMU (AGI-3, Topcon Co., Ltd.) to provide the robot with position and posture data. It is controlled all by CAN bus, which makes the control smoother and more reliable. 2. MATERIALS AND METHODS 2.1 Research Platform – AG1100 The platform of this experiment was AG1100 combine harvester produced by Yanmar Co., Ltd, as is given in Fig 1.
Fig. 1. Platform of the study Specification of the combine harvester is given in Table 1. Table 1. Specification of the combine harvester Length (mm) Width (mm) Height (mm) Engine Output (kW) Crawler Size (mm) Speed (m/s)
6150 2350 2760 80.9 500x1780 Low: 0~1.0 Medium: 0~2.0 High: 0~2.81
This combine harvester can work in both “Manual Mode” and “Automatic Mode”. In “Automatic Mode”, it can be controlled by a computer. All functions of the combine can be performed by sending commands from a computer via a CAN bus. Schematic diagram of the control system of the combine harvester is given in Fig. 2.
Fig. 2. Platform of the study 2.2 Navigation Sensor A Topcon AGI3 GPS+IMU receiver was used in this study, for the reason that it can provide both position and posture data of the combine harvester to the computer. It communicates with the computer via a serial cable, which is commonly used and easy to control. The receiver can output GPS data in various formats, such as GGA, GGK and VTG, etc. By using VRS, its accuracy can be up to ±3cm. Moreover, the posture data is also output by the same serial cable. And the accuracy of the output is about 0.5deg. An advantage of this GPS receiver is that the output of posture data is revised, which solves the problem that the IMU data is always drifting. However, one disadvantage of this receiver is that speed of the vehicle should be great than 0.3m/s when the device is being used. Otherwise, the GPS and IMU would output wrong values. Usually, the GPS and IMU receiver should be mounted to the center of gravity. However, in this study, due to the structure of the combine, the receiver was mounted on the top of the cabin, so as to be closer to the header. Fig.3 is the picture of the device.
Fig. 4. Steering controller 2.4 Navigation Map A navigation map of the robot combine harvester can either be a straight line or a curve. And a map (in a map file) usually consists of a series of points that connected with one another. These connected points together form a navigation map. Each navigation point contains a position that expressed by WGS-84 world coordinate (latitude and longitude). Apart from that a working code is also included. This code contains all the work to do at this point. For example, it contains working status, path number, cutter working status (work or stop) and header’s height (up or down). Besides, a plan file is also required for navigation, which describes the map file name and sequence of the path number. To make a navigation map, it is required that special software should be used. This software can generate a map file and a plan file by using coordinates of the start point and the end point of the first path. Fig.5 is a navigation map used in this study.
Fig. 3. AGI GPS+IMU receiver 2.3 Steering Controller The steering controller of this robot combine harvester can be generalized by Eqn.(1) (1) δ = a1d + a2Δφ where d is the distance from the RTK-GPS receiver to the target path (or lateral error), and Δφ is the difference between current heading and target heading (or heading error). Their definitions are given in Fig. 4. And a1 and a2 are control parameters determined by experiments conducted previously.
Fig. 5. Navigation map 2.5 Experimental Method Navigation of this robot combine harvester was conducted in Ebetsu, Hokkaido, Japan. The objective of this experiment was to test whether the robot could run along a predetermined
straight line and how accurate the combine harvester can run. The GPS coordinates of the straight line were preliminarily measured. And during the navigation, the GPS and IMU data of the combine harvester were recorded. And after the experiment, the accuracy was evaluated.
Fig. 8 Vehicle’s heading error As indicated in Fig. 7 and Fig. 8, with an initial lateral error of 20 cm and an initial heading error of 1.8 degrees, the robot combine harvest could achieve an accuracy described as follows: The maximum absolute value of lateral error was 20 cm, which was the initial lateral error, while the maximum absolute value of heading error was 3.9deg, as the result of the vehicle’s steering to compromise the large initial lateral error. When the vehicle is in a stable situation, the lateral error fluctuated within ±8.3cm , and the heading error fluctuated within ±2.5 degrees. The R.M.S. of the lateral error and the heading error under a stable situation were 3.47 cm and 0.92 degree, respectively. Given that the distance between two rows of wheat or paddy is 33cm in Hokkaido and 30cm in other regions of Japan, this robot combine harvester can be applied in practical wheat and paddy harvesting.
Fig.6. Navigation data Fig. 6 is part of the navigation map and corresponding running data record. The navigation map is in red color and the data recorded is in blue. As in the figure, there is a little shift between the path and the map. This is because that the GPS receiver is not in the geometric center of the combine harvester. When calculating the lateral error, this shift is considered. 3. RESULTS AND DISCUSSION In order to test the accuracy of the combine harvester under stable situation, a long path of over 150 meters was used. The initial lateral error was about 20cm and the initial heading error was about 1.8deg. After startup, the combine harvester headed for the target path with a speed of 1.0m/s. During the test, lateral error and heading error were recorded, as given in Fig. 7 and Fig. 8.
Fig. 9 Robot combine harvester at work 4. CONCLUDING REMARKS
Fig. 7 Vehicle’s lateral error
In this study, a robot combine harvester was developed. This combine harvester can be controlled by sending commands via a CAN bus. In order to record the position and posture of the machine, an RTK-GPS receiver embedded with an IMU
was used. By using data provided by this device, the computer in the combine harvester can calculate lateral and heading error, and then steer the machine. A straight running test was conducted to evaluate the accuracy, and the result showed that this robot can be applied in practical harvesting of wheat and paddy in Japan. REFERENCES Iida, M., Yamada, Y., (2006). Rice harvesting operation using an autonomous combine with a GPS and a FOG, Proceedings of the Conference of Automation Technology for Off-road Eqipment 2006, ASAE, 125131. Matsui. Control of crawler tractor using GPS as navigation sensor, Master Thesis, 2007. Nagasaka, Y., Umeda, N., Kanetani, Y., Taniwaki, K., Sasaki, Y., (2004). Autonomous guidance for rice transplanting using global positioning and gyroscopes, Computers and Electronics in Agriculture, 43, 223-234. Kise, M., Noguchi, N., Ishii, K., Terao, H., (2002). Field mobile robot navigated by RTK-GPS and FOG (Part3), Journal of JSAM, 64(2), 102-110. Takai, R., Barawid, O. Jr., Ishii , K., Noguchi, N., (2010). Development of Crawler-Type Robot Tractor based on GPS and IMU, Preprint of the IFAC International Conference on AGRICONTROL 2010 (CD-R), A3-5. Yang, L., Noguchi, N., Ishii, K., (2012). Development of a Real Time Multi-lens based Omni-directional Stereo Vision, Automation Technology for Off-Road Equipment 2012, 35-40.
Abstract: Currently, the number of farmers in Japan is decreasing at an especially high speed. In addition, the average age of the farmers available is increasing. In this trend, it is entirely possible that several decades later, the self-sufficiency rate of agricultural product in Japan will drop sharply. To solve this problem, one possible solution should be to employ agricultural robot in actual use, including robot tractor, robot combine harvester and so on. Recognizing the importance and urgency of developing such agricultural robots, this study proposed and developed a robot combine harvester. This robot relies on an AGI GPS receiver and IMU for position and posture data. It is controlled via CAN BUS. In this study, its accuracy was tested, and it shows that this combine harvester can be applied in Honshu and Hokkaido area of Japan with this accuracy. Keywords: Robot, Combine Harvester, Path-Plan, GPS, IMU 1. INTRODUCTION In Japan, agriculture is confronted with several serious problems, such as the shortage and aging of labor force. To solve these problems, the Ministry of Agriculture, Forestry and Fishery of Japan (MAFF) has launched a plan to promote the development of robots for agricultural use. This also aims at increasing agricultural productivity and improving selfsufficiency in Japan. Currently, many different types of agricultural robots are under development in Japan, such as a robot wheel-type tractor (Kise et al., 2002, Yang et al., 2012), a robot crawlertype tractor (Takai et al., 2010), a robot rice transplant machine (Nagasaka et al., 2004) and a robot combine harvester (Iida et al., 2011). In all the research mentioned above, a real-time kinematic GPS receiver and an IMU/GPS compass are required. Usually, a GPS receiver alone is not sufficient to ensure that a robot vehicle achieve a precise control (Matsui, 2007), consequently, an IMU or a GPS compass is commonly required as a heading sensor. The goal of this research is to develop a combine harvester with different functions that are eligible to practical crop harvesting, such as wheat and/or paddy harvesting. This combine harvester uses an RTK-GPS embedded with an IMU (AGI-3, Topcon Co., Ltd.) to provide the robot with position and posture data. It is controlled all by CAN bus, which makes the control smoother and more reliable. 2. MATERIALS AND METHODS 2.1 Research Platform – AG1100 The platform of this experiment was AG1100 combine harvester produced by Yanmar Co., Ltd, as is given in Fig 1.
Fig. 1. Platform of the study Specification of the combine harvester is given in Table 1. Table 1. Specification of the combine harvester Length (mm) Width (mm) Height (mm) Engine Output (kW) Crawler Size (mm) Speed (m/s)
6150 2350 2760 80.9 500x1780 Low: 0~1.0 Medium: 0~2.0 High: 0~2.81
This combine harvester can work in both “Manual Mode” and “Automatic Mode”. In “Automatic Mode”, it can be controlled by a computer. All functions of the combine can be performed by sending commands from a computer via a CAN bus. Schematic diagram of the control system of the combine harvester is given in Fig. 2.
Fig. 2. Platform of the study 2.2 Navigation Sensor A Topcon AGI3 GPS+IMU receiver was used in this study, for the reason that it can provide both position and posture data of the combine harvester to the computer. It communicates with the computer via a serial cable, which is commonly used and easy to control. The receiver can output GPS data in various formats, such as GGA, GGK and VTG, etc. By using VRS, its accuracy can be up to ±3cm. Moreover, the posture data is also output by the same serial cable. And the accuracy of the output is about 0.5deg. An advantage of this GPS receiver is that the output of posture data is revised, which solves the problem that the IMU data is always drifting. However, one disadvantage of this receiver is that speed of the vehicle should be great than 0.3m/s when the device is being used. Otherwise, the GPS and IMU would output wrong values. Usually, the GPS and IMU receiver should be mounted to the center of gravity. However, in this study, due to the structure of the combine, the receiver was mounted on the top of the cabin, so as to be closer to the header. Fig.3 is the picture of the device.
Fig. 4. Steering controller 2.4 Navigation Map A navigation map of the robot combine harvester can either be a straight line or a curve. And a map (in a map file) usually consists of a series of points that connected with one another. These connected points together form a navigation map. Each navigation point contains a position that expressed by WGS-84 world coordinate (latitude and longitude). Apart from that a working code is also included. This code contains all the work to do at this point. For example, it contains working status, path number, cutter working status (work or stop) and header’s height (up or down). Besides, a plan file is also required for navigation, which describes the map file name and sequence of the path number. To make a navigation map, it is required that special software should be used. This software can generate a map file and a plan file by using coordinates of the start point and the end point of the first path. Fig.5 is a navigation map used in this study.
Fig. 3. AGI GPS+IMU receiver 2.3 Steering Controller The steering controller of this robot combine harvester can be generalized by Eqn.(1) (1) δ = a1d + a2Δφ where d is the distance from the RTK-GPS receiver to the target path (or lateral error), and Δφ is the difference between current heading and target heading (or heading error). Their definitions are given in Fig. 4. And a1 and a2 are control parameters determined by experiments conducted previously.
Fig. 5. Navigation map 2.5 Experimental Method Navigation of this robot combine harvester was conducted in Ebetsu, Hokkaido, Japan. The objective of this experiment was to test whether the robot could run along a predetermined
straight line and how accurate the combine harvester can run. The GPS coordinates of the straight line were preliminarily measured. And during the navigation, the GPS and IMU data of the combine harvester were recorded. And after the experiment, the accuracy was evaluated.
Fig. 8 Vehicle’s heading error As indicated in Fig. 7 and Fig. 8, with an initial lateral error of 20 cm and an initial heading error of 1.8 degrees, the robot combine harvest could achieve an accuracy described as follows: The maximum absolute value of lateral error was 20 cm, which was the initial lateral error, while the maximum absolute value of heading error was 3.9deg, as the result of the vehicle’s steering to compromise the large initial lateral error. When the vehicle is in a stable situation, the lateral error fluctuated within ±8.3cm , and the heading error fluctuated within ±2.5 degrees. The R.M.S. of the lateral error and the heading error under a stable situation were 3.47 cm and 0.92 degree, respectively. Given that the distance between two rows of wheat or paddy is 33cm in Hokkaido and 30cm in other regions of Japan, this robot combine harvester can be applied in practical wheat and paddy harvesting.
Fig.6. Navigation data Fig. 6 is part of the navigation map and corresponding running data record. The navigation map is in red color and the data recorded is in blue. As in the figure, there is a little shift between the path and the map. This is because that the GPS receiver is not in the geometric center of the combine harvester. When calculating the lateral error, this shift is considered. 3. RESULTS AND DISCUSSION In order to test the accuracy of the combine harvester under stable situation, a long path of over 150 meters was used. The initial lateral error was about 20cm and the initial heading error was about 1.8deg. After startup, the combine harvester headed for the target path with a speed of 1.0m/s. During the test, lateral error and heading error were recorded, as given in Fig. 7 and Fig. 8.
Fig. 9 Robot combine harvester at work 4. CONCLUDING REMARKS
Fig. 7 Vehicle’s lateral error
In this study, a robot combine harvester was developed. This combine harvester can be controlled by sending commands via a CAN bus. In order to record the position and posture of the machine, an RTK-GPS receiver embedded with an IMU
was used. By using data provided by this device, the computer in the combine harvester can calculate lateral and heading error, and then steer the machine. A straight running test was conducted to evaluate the accuracy, and the result showed that this robot can be applied in practical harvesting of wheat and paddy in Japan. REFERENCES Iida, M., Yamada, Y., (2006). Rice harvesting operation using an autonomous combine with a GPS and a FOG, Proceedings of the Conference of Automation Technology for Off-road Eqipment 2006, ASAE, 125131. Matsui. Control of crawler tractor using GPS as navigation sensor, Master Thesis, 2007. Nagasaka, Y., Umeda, N., Kanetani, Y., Taniwaki, K., Sasaki, Y., (2004). Autonomous guidance for rice transplanting using global positioning and gyroscopes, Computers and Electronics in Agriculture, 43, 223-234. Kise, M., Noguchi, N., Ishii, K., Terao, H., (2002). Field mobile robot navigated by RTK-GPS and FOG (Part3), Journal of JSAM, 64(2), 102-110. Takai, R., Barawid, O. Jr., Ishii , K., Noguchi, N., (2010). Development of Crawler-Type Robot Tractor based on GPS and IMU, Preprint of the IFAC International Conference on AGRICONTROL 2010 (CD-R), A3-5. Yang, L., Noguchi, N., Ishii, K., (2012). Development of a Real Time Multi-lens based Omni-directional Stereo Vision, Automation Technology for Off-Road Equipment 2012, 35-40.