Modern agriculture and horticulture are often labor intensive. At the same time, while wages are on the rise, the availability of a skilled workforce that is willing to perform the repetitive tasks in the harsh environmental conditions of a greenhouse, orchard or a field, is decreasing rapidly. Interestingly enough, however, the current state of the art in automated harvesting of fruits and vegetables has remained remarkably stationary in the past decades, in part because of technological barriers that have not been addressed successfully thus far. Contributing to the effort to revolutionize agriculture, our group has been involved in various research projects in agrobotics, focusing on the where agriculture and computer vision meet. What we term agrovision offers challenges that no other domain in computer vision can offers, with tangible potential to aid society as a whole.
While smaller projects preceded it, our first major contribution was in the EU-FP7-project cRops , where extensive research has been performed by the 14 partners on generic robotic solutions for automatic selective harvesting. One of the main applications of cRops was for sweet pepper harvesting, which led to the new EU project SWEEPER – a Sweet Pepper Harvesting Robot. Our goal is to develop a fully autonomous robot that can harvest sweeper peppers in greenhouses 24/7. The project incorporates 6 partners from 4 different countries (The Netherlands, Belgium, Sweden and Israel) and involves experts from a wide-range of disciplines, including horticulture, horticultural engineering, machine vision, sensing, robotics, control, intelligent systems, software architecture, system integration and greenhouse crop management.
B. Arad, J. Balendonc, R. Barth, O. Ben-Shahar, Y. Edan, T. Hellstr, J. Hemming, P. Kurtser, O. Ringdahl, T. Tielen, and B. van Tuijl, Development of a Sweet Pepper Harvesting Robot , Journal of Field Robotics (JFR), Vol. 37, pp. 1027-1039, 2020 (Authors listed alphabetically).
- B. Arad*, P. Kurtser*, E. Barnea, B. Harel, Y. Edan, and O. Ben-Shahar, Controlled lighting and illumination-independent target detection for real-time cost-efficient applications. The case study of sweet pepper robotic harvesting , Sensors, Special issue on Agricultural Sensing and Image Analysis, Vol. 19, pp. 1-15 , 2019 (*=equal contribution).
- E. Barnea, R. Mairon,and O. Ben-Shahar, Colour-Agnostic Shape-Based 3D Fruit Detection for Crop Harvesting Robots , Biosystems Engineering, 146, pp. 57-70, 2016
- R. Berenstein, M. Hocevar, T. Godesa, Y. Edan, and O. Ben-Shahar, Distance Dependent Multimodal Image Registration for Agriculture Tasks , Sensors, 15(8), 20845-20862, 2015.
- R. Berenstein, O. Ben-Shahar, Y. Edan, G. Tone, and M. Hacevar, Image registration for agricultural sensing tasks , In the Proceedings of the Internation Conference on Agricultural Engineering (AgEng), Zurich, Switzerland, July 2014.
- E. Barnea and O. Ben-Shahar, Depth based fruit detection from viewer based pose , In the Proceedings of the Internation Conference on Agricultural Engineering (AgEng), Zurich, Switzerland, July 2014.
- K. Kapach, E. Barnea, R. Mairon, Y. Edan, and O. Ben-Shahar, Computer Vision for Fruit Harvesting Robots – State of the Art and Challenges Ahead , International journal of Computational Vision and Robotics, 3(1/2), 2012.
- R. Berenstrin, O. Ben-Shahar, A. Shapiro, and Y. Edan, Grape clusters and foliage detection algorithms for autonomous selective vineyard sprayer , Intelligent Service Robotics (ISR), 3(4), 233-243, 2010.
- A. Shapiro, E. Korkidi, A. Demri, O. Ben-Shahar, R. Riemer, and Y. Edan, Toward Elevated Agrobotics: An Autonomous Field Robot for Spraying and Pollinating Date Palm Trees , Journal of Field Robotics, 26(6/7), 572-590, 2009.
- A. Shapiro, E. Korkodi, A. Rotenberg, G. Furst, H. Namdar, B. Sapir, M. Mishkin, O. Ben- Shahar, and Y. Edan, A robotic protoype for spraying and pollinating date palm trees, In the Proceedings of the ASME Conference on Engineering Systems Design and Analysis (ESDA), August, 2008.