Trajectory Control and Its Application to Approach a Target: Part I. Development of Trajectory Control Algorithms for an Autonomous Vehicle

Takigawa, Tomihisa; Sutiarso, Lilik; Koike, Masayuki; Kurosaki, Hideto; Hasegawa, Hiroshi

doi:10.13031/2013.9927

Cited by 9 publications

(5 citation statements)

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“…Outdoors, laser rangefinders can detect landmarks with high accuracy and navigate tractors to their target positions [14,15]. A laser-based guidance system was capable of navigating an autonomous vehicle travelling between rows of trees in real time.…”

Section: Introductionmentioning

confidence: 99%

Navigation of an Autonomous Tractor for a Row-Type Tree Plantation Using a Laser Range Finder—Development of a Point-to-Go Algorithm

2015

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Abstract:It is challenging to develop a control algorithm that uses only one sensor to guide an autonomous vehicle. The objective of this research was to develop a control algorithm with a single sensor for an autonomous agricultural vehicle that could identify landmarks in the row-type plantation environment and navigate a vehicle to a point-to-go target location through the plantation. To enable such a navigation system for the plantation system, a laser range finder (LRF) was used as a single sensor to detect objects and navigate a full-size autonomous agricultural tractor. The LRF was used to control the tractor as it followed a path, and landmarks were detected "on-the-go" in real time. The landmarks were selected based on data for their distances calculated by comparison with the surrounding objects. Once the landmarks were selected, a target point was calculated from the landmarks, and the tractor was navigated toward the target. Navigation experiments were successfully conducted on the selected paths without colliding with the surrounding objects. A real time kinematic global positioning system (RTK GPS) was used to compare the positioning between the autonomous control and manual control. The results of this study showed that this control system could navigate the autonomous tractor to follow the paths, and the vehicle position differed from the manually driven paths by 0.264, 0.370 and 0.542 m for the wide, tight, and U-turn paths, respectively, with directional accuracies of 3.139°, 4.394°, and 5.217°, respectively, which are satisfactory for the autonomous operation of tractors on OPEN ACCESSRobotics 2015, 4 342 rubber or palm plantations. Therefore, this laser-based landmark detection and navigation system can be adapted to an autonomous navigation system to reduce the vehicle`s sensor cost and improve the accuracy of the positioning.

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Section: Introductionmentioning

confidence: 99%

Navigation of an Autonomous Tractor for a Row-Type Tree Plantation Using a Laser Range Finder—Development of a Point-to-Go Algorithm

2015

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“…by Cariou et al (2008; or Zhou et al (2005). The four wheel steering is a common choice in many research prototypes developed for autonomous agricultural robot operations in research institutes (Bak and Jacobsen, 2004;Takigawa et al, 2002;Jørgensen et al, 2007;Ruckelshausen et al, 2009;Bakker et al, 2010;Godoy et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Guidance system for agricultural tractor with four wheel steering

Oksanen

Backman

2013

IFAC Proceedings Volumes

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“…A priori knowledge of the desired path is useful in calculating yaw acceleration and lateral acceleration, which can then be used to calculate steering angles (Vanderploeg et al, 1988). sensing errors or disturbances (Takigawa et al, 2002).…”

Section: Path Trackingmentioning

confidence: 99%

“…However, feedback compensation is still necessary to correct for modeling errors and disturbances (Shin et al, 1992). Takigawa et al (2002) used a feedforward algorithm to calculate steering angles necessary to track a predetermined path, while using feedback control to correct for errors in posture estimation. DeSantis (1995) designed a general, path-tracking controller for either two-wheel or four-wheel steer vehicles capable of guiding along planned paths.…”

Section: Path Trackingmentioning

confidence: 99%

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Development of topographic maps and rear steering control for an agricultural vehicle through incorporation of posture and attitude measurements

Westphalen¹

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A self-propelled agricultural sprayer was equipped with four RTK DGPS receivers and an inertial measurement unit (IMU) to measure vehicle attitude and field elevation as the vehicle was driven across a field. Data was collected in astop-and-go fashion at 3.05 m (10 ft) intervals, as well as in a continuous fashion at three different speed levels on a 2.3 ha field area with varying topography. Pitch and roll bias angles were estimated to within 95% confidence intervals that ranged from 0.01 ° to 0.10°. Using ordinary kriging, digital elevation models (OEMs) were interpolated using only elevation measurements, as well as a combination of elevation and vehicle attitude measurements. The resulting OEMs were compared to each other to evaluate the effect of including attitude measurement on DEM accuracy. At the widest measurement swath width, the OEMs generated with attitude measurements had substantially lower error measures than those OEMs generated without attitude measurements. Vehicle speed affected DEM error, but no discernable trends were detected. These results provide evidence that support the feasibility of using vehicle-based measurements collected during typical field operations for accurate DEM development.

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Trajectory Control and Its Application to Approach a Target: Part I. Development of Trajectory Control Algorithms for an Autonomous Vehicle

Cited by 9 publications

References 0 publications

Navigation of an Autonomous Tractor for a Row-Type Tree Plantation Using a Laser Range Finder—Development of a Point-to-Go Algorithm

Navigation of an Autonomous Tractor for a Row-Type Tree Plantation Using a Laser Range Finder—Development of a Point-to-Go Algorithm

Guidance system for agricultural tractor with four wheel steering

Development of topographic maps and rear steering control for an agricultural vehicle through incorporation of posture and attitude measurements

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