Autopilot for a combine harvester

Coen, T.; Vanrenterghem, A.; Saeys, Wouter; Baerdemaeker, Josse De

doi:10.1016/j.compag.2008.01.014

Cited by 27 publications

(11 citation statements)

References 7 publications

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“…Several studies reported on tractors and combined harvester guidance systems. A tilling robot guided by a laser range finder (Matsuo, Yamamoto, & Yukumoto, 2002;Yukumoto & Matsuo, 1995), GPS-guided tractor (Bell, 2000;Gan-Mor, Clark, & Upchurch, 2007), laser sensor-guided tractor , vision-guided tractor (Billingsley & Schoenfisch, 1997), stereo vision-guided tractor (Kise, Zhang, & Rovira-Más, 2005;Rovira-Más, Zhang, & Reid, 2004, 2008, vision and laser radar-guided tractor (Subramanian, Burks, & Arroyo, 2006), 2D scanner-guided tractor between orchard trees (Barawid, Mizushima, Ishii, & Noguchi, 2007), vision-guided combine harvester (Benson, Reid, & Zhang, 2003), GPS-guided combine harvester (Coen, Vanrenterghem, Saeys, & De Baerdemaeker, 2008), and GPS-guided combine harvester (Iida & Yamada, 2006) were developed. There are studies about tractor implement control (Leemans & Destain, 2007;Tellaechea, BurgosArtizzub, Pajaresc, Ribeirob, & Fernández-Quintanillad, 2008;Tian, Reid, & Hummel, 1999).…”

Section: Introductionmentioning

confidence: 99%

An autonomous rice transplanter guided by global positioning system and inertial measurement unit

Nagasaka

Saito

Tamaki

et al. 2009

Journal of Field Robotics

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This paper reports the development of an automated rice transplanter guided by a global positioning system and an inertia measurement unit using the controller area network bus. The actuator control command and data communication protocols comply with the ISO 11783. The project aims to develop an autonomous agricultural system for operation in the paddy field. The automated rice transplanter presented in this paper is the first stage in achieving the project objective. This paper focuses on the development of sensor and main computer connections to the operating autonomous unit and the use of common control protocols for each of the automated machines. A simple steering control algorithm was used for straight traveling. The automated rice transplanter made a turn at the headland of the paddy field and moved to the next desired path. After 12 straight operations, the rms lateral deviation was observed to be less than 0.04 m and the rms heading angle error was less than 3.6 deg. C 2009 Wiley Periodicals, Inc.

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Section: Introductionmentioning

confidence: 99%

An autonomous rice transplanter guided by global positioning system and inertial measurement unit

Nagasaka

Saito

Tamaki

et al. 2009

Journal of Field Robotics

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“…Machine vision is widely used for autonomous guidance by detecting crop rows (Åstrand & Baerveldt, ; Billingsley & Schoenfisch, ; Han, Zhang, Ni, & Reid, ; Kise, Zhang, & Rovira‐Más, ; Xue, Zhang, & Grift, ). Alternatively, a laser range finder (LRF) is commonly used (Barawid, Mizushima, Ishii, & Noguchi, ; Chateau, Debain, Collange, Trassoudaine, & Alizon, ), swath detection (Coen, Vanrenterghem, Saeys, & De Baerdemaeker, ), or obstacle avoidance (Kise, Zhang, & Noguchi, ). The method of sensor fusion has also been shown to be a promising technique for autonomous guidance (Subramanian, Burks, & Arroyo, ).…”

Section: Introductionmentioning

confidence: 99%

Rice Autonomous Harvesting: Operation Framework

Kurita

Iida

Cho

et al. 2017

Journal of Field Robotics

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This paper reports on an operation framework for autonomous rice harvesting. We developed an integrated algorithm for robotic operation and cooperation with farmworkers to automate each subsection of the harvesting and unloading process and of the processes that bridge them (homing and restarting). The algorithm was installed into a head‐feeding combine robot. The robot followed a target path based on its absolute position and orientation, planning a counterclockwise spiral path in a rectangular paddy field, and returned to a position close to a farm road when its grain tank was filled to a specified level. The grain unloading operation was automated using a machine vision system. As the restarting process (return to harvesting) was also automated, the combine robot was able to harvest a rectangular field autonomously by cyclically repeating the harvesting, homing, unloading, and restarting operations. Under field conditions, the robot was able to follow the target path within tolerable lateral and azimuth errors while harvesting rice successfully, and to unload the harvested grain into a wagon without spillage. The root mean square error of the lateral and azimuth errors during harvesting were 0.04 m and 2.6°, respectively. In the homing operation, the robot returned to a given line within ± 0.1 m and aligned its heading to the direction of the line within ± 4°. The robot recognized the arbitrarily parked wagon and positioned its auger spout at the target point with a respective horizontal and vertical accuracy of ± 0.2 m and ± 0.3 m. Harvesting time accounted for 50%–60% of the entire robotic operation. Homing scheduling and dispatch control for the wagon were found to be of importance for developing a more efficient robotic operation.

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“…In case of measurements of 'larger' distances (in order of metres, tens and hundreds of metres, up to kilometres) phase and pulse rangefinders are used. For example agricultural machines are equipped (experimentally) with laser rangefinders (in the form of laser scanners) (Coen et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Examination Method of the Effect of the Incidence Angle of Laser Beam on Distance Measurement Accuracy to Surfaces With Different Colour and Roughness

Daliga

Kurałowicz

2016

Bol. Ciênc. Geod.

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Interest in the influence of the incidence angle of a laser beam to distance measurements can be seen in many areas of science and technology: geodesy, glaciology, archaeology, machine automation, and others. This paper presents results of measurements of the effect of the incidence angle of a laser beam to distance measurements to the surfaces of different colour and roughness by Topcon's electro-optical total station with an accuracy of 3 mm. Measurement method and the method of elimination of test stand errors are presented. The results of measurements have been analysed and the influence of selected factors (surface colour and roughness, lack of instrument rectification) on the distance measurement have been discussed. It is also shown the critical incidence angle above which it can be impossible to measure distances to reflective foil with tested total station

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Autopilot for a combine harvester

Cited by 27 publications

References 7 publications

An autonomous rice transplanter guided by global positioning system and inertial measurement unit

An autonomous rice transplanter guided by global positioning system and inertial measurement unit

Rice Autonomous Harvesting: Operation Framework

Examination Method of the Effect of the Incidence Angle of Laser Beam on Distance Measurement Accuracy to Surfaces With Different Colour and Roughness

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