DOI QR코드

DOI QR Code

Development of Unmanned Driving Technologies for Speed Sprayer in Orchard Environment

과수원 환경에서의 방제기 무인주행 기술 개발

  • Received : 2020.09.02
  • Accepted : 2020.10.22
  • Published : 2020.12.31

Abstract

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

Keywords

References

  1. FS.G. Vougioukas, "Agricultural Robotics," Annual Review of Control, Robotics, and Autonomous Systems Vol. 2, pp. 365-392, 2019. https://doi.org/10.1146/annurev-control-053018-023617
  2. M. Gang, H.J. Kim, C.W. Jeon, C. Yun, "Preliminary Study on Development of Path Generation and Tracking Algorithms for Autonomous Rice Transplant," Proceedings of Agricultural Machinery, Vol. 24, No. 2, pp. 27-27, 2019 (in Korean).
  3. Benjamin Cates, "A Study to Consider the Specification of Posture Sensor for Autonomous Tractor," The korean society of machanical engineers conference, 2018.
  4. Mai, X, Zhang, H, Jia, X., Meng, M. Q. H. "Faster R-CNN With Classifier Fusion for Automatic Detection of Small Fruits," IEEE Transactions on Automation Science and Engineering, 2020.
  5. Berenstein. R, Y. Edan, "Automatic Adjustable Spraying Device for Site-specific Agricultural Application," IEEE Transactions on Automation Science and Engineering, Vol. 15, No. 2, 641-650, 2017. https://doi.org/10.1109/TASE.2017.2656143
  6. D.K. Giles, M.J. Delwiche, R.B. Dodd, "Control of Orchard Spraying Based on Electronic Sensing of Target Characteristics," Transactions of the ASAE, Vol. 30, No. 6, pp. 1624-1636, 1987. https://doi.org/10.13031/2013.30614
  7. G.D. Hong, J. Park, "Novel Embedded OS for Soccer Robot System," IEMEK J. Embed. Sys. Appl., Vol. 1, No. 1, pp. 1-12, 2004 (in Korean).
  8. J Llorens, E Gil, J Llop, "Ultrasonic and LIDAR Sensors for Electronic Canopy Characterization in Vineyards: Advances to Improve Pesticide Application Methods," Sensors, Vol. 11, No. 2, pp. 2177-2194, 2011. https://doi.org/10.3390/s110202177
  9. B. Boyd, A. John, V.H. Mellencamp, Handbook of Embedded Control Systems, SIAM, Philadelphia, 2005.
  10. J. Park, P. Kim, "Implementation of Embedded Software for Mobile Robot," Proceedings of 3rd Asian Embedded Systems Conference, Vol. 2, pp. 100-105, 2006.
  11. A Segal, D Haehnel, S Thrun, "Generalized-icp," Robotics: science and systems, Vol. 2, No. 4, pp. 435, 2009.
  12. J Weingarten, R Siegwart, "EKF-based 3D SLAM for Structured Environment Reconstruction," 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2005.
  13. A. Asvadi, C Premebida, P Peixoto, U Nunes, "3D Lidar-based Static and Moving Obstacle Detection in Driving Environments: An Approach Based on Voxels and Multi-region Ground Planes," Robotics and Autonomous Systems Vol. 83, pp. 299-311, 2016. https://doi.org/10.1016/j.robot.2016.06.007
  14. D Bradley, G Roth, "Adaptive Thresholding Using the Integral Image," Journal of graphics tools Vol. 12, No. 2, pp. 13-21, 2007 https://doi.org/10.1080/2151237X.2007.10129236
  15. I Afanasyev, A Sagitov, E Magid, "ROS-based SLAM for a Gazebo-simulated Mobile Robot in Image-based 3D Model of Indoor Environment," International Conference on Advanced Concepts for Intelligent Vision Systems, pp. 273-283, 2015.