Call for Papers: IEEE RA-L Special Issue on Precision Agricultural Robotics and Autonomous Farming Technologies


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. 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)

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


Special Issue Submission Opens: 17 February 2018
Special Issue Submission Deadline: 25 February 2018 (same as RAL/IROS)
First Decision Communicated to Authors: 21 May 2018
Final Decision Communicated to Authors: 25 July 2018
Accepted RAL Papers appear on IEEEXplore: 23 August 2018

Conference Option

This Special Issue will be associated with the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1-5 October 2018 in 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.

How to submit

Authors will be available to submit your papers to our special issue via RAS paperplaza (RA-L submission system). There will be a menu on the submission system for our SI, Precision Agricultural Robotics and Autonomous Farming Technologies. But the submission system will be opened on 17 February 2018, and will be closed on 24 February 2018. So please keep in mind the submission is only available from 17 February 2018 for one week.


Advisory Committee

Bruce MacDonald (University of Auckland, New Zealand)
Roland Siegwart (ETH Zurich, Switzerland)
Peter Corke (Queensland University of Technology, Australia)


Ho Seok Ahn, corresponding organizer - This email address is being protected from spambots. You need JavaScript enabled to view it., University of Auckland, New Zealand
Inkyu Sa - This email address is being protected from spambots. You need JavaScript enabled to view it., ETH Zurich, Switzerland
Feras DayoubThis email address is being protected from spambots. You need JavaScript enabled to view it., Queensland University of Technology, Australia

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