Overview of Sensor Technologies Used for 3D Localization of Asparagus Spears for Robotic Harvesting

Abstract:

Article Preview

Advances in agricultural automation, coupled with a general decline of available labour hasgenerated interest in automated harvesting of various crops. Paramount to the success of such systemsis the development of accurate, robust detection technologies and localization strategies. This paperpresents an overview of sensor technologies used in the detection and localization of green aspara-gus spears for robotic harvesting. Tactile, photoelectric, machine vision and time-of-flight sensors areinvestigated and their applicability for use in robotic asparagus harvesting is evaluated. Investigationof previous asparagus harvesting devices has revealed that no such device has yet achieved commer-cial viability. It was identified that this is likely due to weaknesses in currently employed detectiontechnologies, namely slow response times, high sensitivity to changes in ambient lighting conditionsand requirement for frequent manual calibration. Of the sensor technologies investigated it was foundthat time-of-flight cameras, such as the Microsoft Kinect V2 are the most feasible for the detectionof asparagus spears for robotic harvesting. It was concluded that further research would be conductedinto the application of such sensors into a commercially viable harvester.

Info:

Periodical:

Edited by:

Leandro Bolzoni

Pages:

77-85

Citation:

M. Peebles et al., "Overview of Sensor Technologies Used for 3D Localization of Asparagus Spears for Robotic Harvesting", Applied Mechanics and Materials, Vol. 884, pp. 77-85, 2018

Online since:

August 2018

Export:

Price:

$38.00

* - Corresponding Author

[1] LLP, A.R., Agricultural Robots Market Analysis &; Trends - Product, Technology - Forcast to 2025. 2016. p.113.

[2] Lewis, G., Personal Communication, M. Peebles,(2016).

[3] Du, C., Z. Qin, and W. Shumao, Current Status and Technical Challenges of Asparagus Mechanical Harvesting. 2010 Pittsburgh, Pennsylvania, June 20 - June 23, (2010).

DOI: https://doi.org/10.13031/2013.29743

[4] Matteoli, A.J., Asparagus harvester. 1952, Google Patents.

[5] Turkington, J.O., Asparagus harvesting machine. 1956, Google Patents.

[6] Haws, S.K., Stalk selective harvesting machine. 1977, Google Patents.

[7] Arndt, G., R. Rudziejewski, and V.A. Stewart, On the future of automated selective asparagus harvesting technology. Computers and Electronics in Agriculture, 1997. 16(2): pp.137-145.

DOI: https://doi.org/10.1016/s0168-1699(96)00033-6

[8] Lund, W.J., Asparagus harvester. 1985, Google Patents.

[9] Haws, S.K.R., WA, US, Selective Harvester. 2010: United States.

[10] Clary, C.D., et al., Performance and economic analysis of a selective asparagus harvester. Applied Engineering in Agriculture, 2007. 23(5): pp.571-577.

[11] Humburg, D.S. and J.F. Reid, A machine vision algorithm for identification of harvestable spears of asparagus. 1990. p. 13pp.

[12] Humburg, D.S. and J.F. Reid. Field performance of machine vision for the selective harvest of asparagus. in International Off-Highway and Powerplant Congress and Exposition, September 9, 1991 - September 12, 1991. 1991. Milwaukee, WI, United states: SAE International.

DOI: https://doi.org/10.4271/911751

[13] Irie, N., et al., Asparagus Harvesting Robot Coordinated with 3-D Vision Sensor. 2009 Ieee International Conference on Industrial Technology, Vols 1-3, 2009: pp.408-413.

DOI: https://doi.org/10.1109/icit.2009.4939556

[14] Mehta, S.S. and T.F. Burks, Multi-camera Fruit Localization in Robotic Harvesting. IFACPapersOnLine, 2016. 49(16): pp.90-95.

DOI: https://doi.org/10.1016/j.ifacol.2016.10.017

[15] Jones, M., Personal Communication, M. Peebles,(2016).

[16] Baylou, P., et al., Detection and three-dimensional localization by stereoscopic visual sensor and its application to a robot for picking asparagus. Pattern Recognition, 1984. 17(4): pp.377-384.

DOI: https://doi.org/10.1016/0031-3203(84)90067-0

[17] Bousseau, G., et al., Automatic asparagus picking machine. 1984, Google Patents.

[18] Grattoni, P., et al. Automatic harvesting of asparagus: an application of robot vision to agriculture. (1994).

[19] Strauß, J., Development of an Automatic harvesting system for green asparagus with stalk detection in Ambient Light. 2014. pp.1-14.

[20] Sakai, H., et al., Accurate position detecting during asparagus spear harvesting using a laser sensor. Engineering in Agriculture, Environment and Food, 2013. 6(3): pp.105-110.

DOI: https://doi.org/10.1016/s1881-8366(13)80019-5

[21] Irie, N. and N. Taguchi, Asparagus harvesting robot. Journal of Robotics and Mechatronics, 2014. 26(2): pp.267-268.

[22] Luna, C.A., et al., Robust people detection using depth information from an overhead Time-ofFlight camera. Expert Systems with Applications, 2017. 71: pp.240-256.

DOI: https://doi.org/10.1016/j.eswa.2016.11.019

[23] Stahlschmidt, C., et al., Applications for a people detection and tracking algorithm using a timeof- flight camera. Multimedia Tools and Applications, 2016. 75(17): pp.10769-86.

DOI: https://doi.org/10.1007/s11042-014-2260-3

[24] Kapuciski, T., M. Oszust, and M. Wysocki. Hand gesture recognition using time-of- flight camera and viewpoint feature histogram. in 11th International Conference on Diagnostics of Processes and Systems, DPS 2013, September 8, 2013 - September 11, 2013. 2014. Lubuski, Poland: Springer Verlag.

DOI: https://doi.org/10.1007/978-3-642-39881-0_34

[25] Oprisescu, S., C. Burlacu, and V. Buzuloiu. Action Recognition using Time of Flight Cameras. in 2010 8th International Conference on Communications (COMM), 10-12 June 2010. 2010. Piscataway, NJ, USA: IEEE.

DOI: https://doi.org/10.1109/iccomm.2010.5509074

[26] Sun, L., J.-R. Cai, and J.-W. Zhao, Vision System Based on TOF 3D Imaging Technology Applied to Robotic Citrus Harvesting. Intelligent Automation &; Soft Computing, 2015: pp.1-10.

DOI: https://doi.org/10.1080/10798587.2015.1015767

Fetching data from Crossref.
This may take some time to load.