Precision Agricultural Robotics and Autonomous Farming Technologies

A Special Issue organized by H. S. Ahn, I. Sa, and F. Dayoub

Published Papers

1. S. Ahn, I. Sa, and F. Dayoub, “Introduction to the Special Issue on Precision Agricultural Robotics and Autonomous Farming Technologies,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 4435–4438, Oct. 2018, doi: 10.1109/LRA.2018.2871803.
2. Chebrolu, T. Lbe, and C. Stachniss, “Robust long-term registration of UAV images of crop fields for precision agriculture,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3097–3104, Oct. 2018, doi: 10.1109/LRA.2018.2849603.
3. A. Miranda, J. Davidson, R. M. Johnson, H. Wagues-pack, and I. Hermano Krebs, “Robotics for sugarcane cultivation: Analysis of billet quality using computer vision,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3828– 3835, Oct. 2018, doi: 10.1109/LRA.2018.2856999.
4. Halstead, C. McCool, S. Denman, T. Perez, and C. Fookes, “Fruit quantity and ripeness estimation using a robotic vision system,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 2995–3002, Oct. 2018, doi: 10.1109/LRA.2018.2849514.
5. Lottes, J. Behley, A. Milioto, and C.Stachniss, “Fully convolutional networks with sequential information for robust crop and weed detection in precision farming,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 2870–2877, Oct. 2018, doi: 10.1109/LRA.2018.2846289.
6. Imperoli, C. Potena, D. Nardi, G. Grisetti, and A. Pretto, “An effective multi-cue positioning system for agricultural robotics,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3685–3692, Oct. 2018, doi: 10.1109/LRA.2018.2855052.
7. Bosilj, T. Duckett, and G. Cielniak, “Analysis of morphology-based features for classification of crop and weeds in precision agriculture,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 2950–2956, Oct. 2018, doi: 10.1109/LRA.2018.2848305.
8. Heo, S. Kim, D. Kim, K. Lee, and W. Chung, “Super-high-purity seed sorter using low-latency image-recognition based on deep learning,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3035–3042, Oct. 2018, doi: 10.1109/LRA.2018.2849513.
9. Winterhalter, F. Veronika Fleckenstein, C. Dornhege, and W. Burgard, “Crop row detection on tiny plants with the pattern hough transform,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3394–3401, Oct. 2018, doi: 10.1109/LRA.2018.2852841.
10. Pulido Fentanes, L. Gould, T. Duckett, S. Pearson, and G. Cielniak, “3D soil compaction mapping through kriging-based exploration with a mobile robot,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3066–3072, Oct. 2018, doi: 10.1109/LRA.2018.2849567.
11. Hughes, L. Scimeca, L. Ifrim, P. Maiolino, and F. Iida, “Achieving robotically peeled lettuce,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 4337–4342, Oct. 2018, doi: 10.1109/LRA.2018.2855043.
12. Ambrozio Dias, A. Tabb, and H. Medeiros, “Multi-species fruit flower detection using a refined semantic segmentation network,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3003–3010, Oct. 2018, doi: 10.1109/LRA.2018.2849498.
13. Flecher, V. Cadenat, T. Sentenac, and S. Vougioukas, “Tree detection with low-cost 3D sensors for autonomous navigation in orchards,” IEEE Robot. Autom. Lett., vol. 3, no. 4, pp. 3876–3883, Oct. 2018, doi: 10.1109/LRA.2018.2857005.

Topical Area

This special issue on RA-L will focus on current advances in the area of autonomous farming.
Papers are solicited on all areas directly related to these topics, including but not limited to:

• Robots for pruning, thinning, harvesting, mowing, spraying, and weed removal
• Aerial and ground robotic platforms for soil/crop monitoring, prediction, and decision making
• Aerial Robotics for Environmental and Agricultural applications
• Sensing and yield-estimation in precision agriculture
• Fruit and flower detection and recognition
• Approaches to cost-effective sensing for day/night continuous operation
• Long-term autonomy and navigation in unstructured farming environments
• Manipulators and platforms for soil preparation, seeding, crop protection, and harvesting
• Adaptive sampling and informative data collection
• Adaptive technologies that manage plants, soil or animals according to as-sensed status
• Theoretical and empirical decision-oriented data-analysis techniques including machine learning

Motivation and Endorsements

Growth in world population, increasing urbanization and changing consumption habits means demand for food production is predicted to increase dramatically over the coming decades. This increased demand in food production must be achieved despite challenges such as climate change, a limited supply of new arable land and difficulties in sourcing skilled farm labour. Robotics and automation are likely to play a key role in meeting these challenges over the coming decades by helping to improve farm productivity. A key component of these future autonomous agricultural systems is the development of robust and accurate perception systems for perceiving the agricultural environment. Recently, the development of these agricultural perception systems in both research and industry has been spurred on by the emergence of new and increasingly cost-effective sensing modalities such as multi- and hyperspectral imaging, high resolution cameras, LiDAR, radar and centimetre precision GPS. These sensing modalities have been complemented by advances in the size and affordability of computing power and increasingly capable algorithms. Following up recent activity, IROS 2016 special sessions on Autonomous Farming Technologies and Agricultural Robotics (Oct 9, 2016), we would like to extend and draw researchers’ attention on Agricultural Robotics and Autonomous Farming Technologies.This special issue is supported by IEEE RAS Agricultural Robotics and Automation Technical Committee (TC-AgRa) and IEEE-RAS Technical Committee on Mobile Manipulation (TCMM)

Timeline

1. Special Issue Call Publication: December 30, 2017
   
2. Special Issue Submission Opens: February 17, 2018
3. Special Issue Submission Closes: February 24, 2018 (same as RAL/IROS)
4. First Decision Communicated to Authors: May 21, 2018
5. Final Decision Communicated to Authors: July 25, 2018
6. Accepted RAL Papers appear on Xplore: August 23, 2018

Conference Option

The Special Issue will be associated with the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 1-5, 2018, Madrid, Spain and accepted articles will be presented at the conference. Authors of submissions commit that, if accepted by the IROS Program Committee, they will present the work at IROS.