Present and Future of Agricultural Robotics and Technologies: Academic and Industry Perspectives

Increasing population, decreasing arable land, climate change, and a declining skilled workforce pose unprecedented challenges to the ability to satisfy the growing demand for food on a global scale. It is thus becoming more and more important to increase or at the very least maintain current productivity while using fewer inputs, such as water and agrichemicals.  Precision agriculture (PA) aims to address this issue.  In recent years there has been a boom in agricultural robotics and allied technology (e.g., vegetation-specific sensors) employed within PA routines.  Such efforts have so far been undertaken in a rather decoupled manner.  However, several research labs (both in academic and private sector settings) around the world are increasingly co-designing actuation and perception systems, to help introduce the agricultural robots of the future.  

This workshop aims to highlight and in turn help push forward co-design of actuation and perception efforts for future agricultural robotics.  Its main objective is to bring together researchers that focus on robotics and sensor technologies, and who are situated both within academia and industry.  Doing so will create stronger links between both ends.  Academic researchers will have the opportunity to learn more about specific technologies that are already field-ready while industry partners will gather more detailed information about some key current challenges holding back agricultural robotics research that may not be possible to resolve in a scalable manner within the limits of academic research.

The main objective of the workshop is to bring together researchers that focus on robotics and sensor technologies, and who are situated both within academia and industry.  To support this objective, we feature diverse invited talks by speakers from academia, government, and industry.  To better promote exchange of ideas and engage the attendees, the workshop also features a call for extended abstracts, a call for demos, and a panel discussion.  We anticipate that this way we can reach out to a more diverse audience that includes both researchers in academia as well as practitioners and researchers in the private sector (and help increase the participation of those communities in IROS’23 as a whole).

• Broader participants are invited to submit extended abstracts (2 pages max).  Accepted abstracts (to be peer-reviewed by the workshop organizers) will be presented during the workshop in a poster format.  In addition, poster presenters will also give lighting talks (3-min long) to promote their work.  

• Broader participants may also choose to present a demo in addition to or instead of a poster presentation. We anticipate that live demos will help demonstrate some key results, or highlight current challenges (negative results that can spark interesting discussions are considered as well).

In all, the workshop will feature:

• 9 invited talks over four sessions

• 16 posters over two sessions (also lighting talks) 

• 1 panel discussion

• Konstantinos Karydis, PhD

  • Associate Professor, Electrical and Computer Engineering, University of California, Riverside (UCR), Riverside, CA 92507, USA

  • Web: https://arcslab.org/

  • Email: kkarydis@ece.ucr.edu

• Stefano Carpin, PhD

  • Professor, Computer Science and Engineering, University of California, Merced (UCM), Merced, CA 95343, USA

  • Web: https://robotics.ucmerced.edu/

  • Email: scarpin@ucmerced.edu

• Stavros Vougioukas, PhD

  • Professor of Biological and Agricultural Engineering, University of California, Davis (UCD), Davis, CA 95616, USA

  • Web: https://faculty.engineering.ucdavis.edu/vougioukas/

  • Email: svougioukas@ucdavis.edu

• Cyrill Stachniss, PhD

  • Full Professor, Institute of Geodesy and Geoinformation, University of Bonn (UBonn), Bonn, 53115, Germany

  • Web: https://www.ipb.uni-bonn.de/

  • Email: cyrill.stachniss@igg.uni-bonn.de

• Dimitris Zermas; Principal Scientist, Sentera  

• Charlie Andersen; CEO, Burro  

• Kyle Coble, Farm-Ng 

• Steven Thomson; National Program Leader, USDA-NIFA 

• Cherie Kagan; Professor, Electrical and Systems Engineering, University of Pennsylvania  

• Yu Gu; Associate Professor, Mechanical and Aerospace Engineering, West Virginia University  

• David Cappelleri; Professor, Mechanical Engineering, Purdue University 

• Katherine Driggs-Campbell; Assistant Professor, Electrical and Computer Engineering, University of Illinois Urbana-Champaign 

• Marija Popović; Junior Research Group Leader, University of Bonn 

   8:30 – 08:40     Welcome

   8:40 – 09:30     Invited Talks Session 1

• Cherie Kagan, University of Pennsylvania, IoT4Ag's Sensors and Systems for Precision Agriculture

• David Cappelleri, Purdue University, P-AgBot: In-Row & Under-Canopy Agricultural Robot for Monitoring and Physical Sampling

   9:30 – 10:00     Lightning Poster Talks Session 1 (eight presentations, 3 min each - see information below)

10:00 – 11:00     Coffee Break & Poster Session 1

11:00 – 12:30     Invited Talks Session 2

• Dimitris Zermas, Sentera, Lessons from the Field: Deep Learning, Data Curation, and Customer Adoption in Agricultural Robotics

• Kyle Coble, Farm-Ng, Building Real Robots for Real Farms

• Charlie Andersen, Burro.ai,  The Path towards Autonomous Farming – Horizontal Platforms or verticalStacks?

12:30 – 13:30     Lunch

13:40 – 14:30     Invited Talks Session 3

• Marija Popović, University of Bonn, UAV-based Active Perception for Agricultural Robotics

• Katherine Driggs-Campbell, University of Illinois Urbana-Champaign, Monitoring and Managing Multiple Agbots

14:30 – 15:00     Lightning Poster Talks Session 2  (eight presentations, 3 min each - see information below)

15:00 – 16:00     Coffee break & Poster Session 2

16:00 – 16:50     Invited Talks Session 4

• Yu Gu, West Virginia University, The development of a multiple armed precision pollination robot

• Steven Thomson, USDA, Outlook for funding robotics research at the USDA-NIFA

16:50 – 17:25     Panel

17:25 – 17:30     End

Session 1

1. Informative path planning for scalar dynamic reconstruction using coregionalized Gaussian processes and a spatiotemporal kernel, by Lorenzo A Booth, Stefano Carpin (University of California - Merced)

2. Robotic Pollination of Apples in Commercial Orchards, by Ranjan Sapkota, Dawood  Ahmed Salik Khanal, Uddhav Bhattarai, Changki Mo, Matthew  Whiting, Manoj Karkee (Washington State University)

3. Robust navigation in arboreal environments without GNSS, by Miguel Torres-Torriti (Pontificia Universidad Catolica de Chile); Paola Nazate-Burgos (Pontificia Universidad Catolica de Chile); Fernando Auat Cheein (Universidad Tecnica Federico Santa Maria)

4. Operational Space Control with Reinforcement Learning Redundancy Resolution for Agricultural Manipulators, by Miguel Torres-Torriti, Hector Garces (Pontificia Universidad Catolica de Chile); Fernando Auat Cheein (Universidad Tecnica Federico Santa Maria)

5. A machine learning strategy for weed detection on grassfields, by Miguel Torres-Torriti, Felipe Calderara-Cea (Pontificia Universidad Catolica de Chile); Fernando Auat Cheein (Universidad Tecnica Federico Santa Maria); Jose Delpiano (University of the Andes)

6. Agrifood Detection Enhancement with Synthetic Data, by Xiaomin Lin (University of Maryland)

7. Fusion-Driven Tree Reconstruction and Fruit Localization: Advancing Precision in Agriculture, by Kaiming Fu, Peng Wei, Juan Villacres (University of California - Davis)

8. Geo-referenced 3-D mapping of vineyards using factor graph and CNN-based depth estimation, by Thiago Santos, Luciano V Koenigkan (Embrapa Agricultural Informatics)

Session 2

1. Walnut Detection Through Deep Learning Enhanced by Multispectral Synthetic Images, by Kaiming Fu (University of California - Davis)

2. Cloud-E: Cloud-Enabled Robotic Solution for Smart Nitrogen Management In Precision Agriculture, by Ankita Kalra (University of Nebraska Lincoln)

3. Comparative Analysis of Lidar Odometry Algorithms in Blueberry Crops, by Clayder A Gonzalez; Ricardo Jesus Huaman Kemper, Sixto Ricardo Prado Gardini (Universidad Privada Antenor Orrego)

4. Deep Learning Approach for Accurate Pre-Harvest Blueberry Ripeness Classification, by Percy B Cubas, Ricardo Jesus Huaman Kemper, Sixto Ricardo Prado Gardini (Universidad Privada Antenor Orrego)

5. Multi-UAV Slung Load Carrying for Methane Emissions Measurement, by Harvey Merton (Massachusetts Institute of Technology)

6. Obstacle Aware Flight Planning with Optimal Control for UAV to Track Dynamic Trajectory, by Veera Venkata Ram Murali Krishna Rao Muvva, Kunjan Theodore Joseph, Santosh Pitla (University of Nebraska Lincoln)

7. AlphaGarden-NeRF: 3D Representation for Plant Growth Monitoring, by Simeon O.Adebola, Adam  B Rashid , Zehan  Ma, Roy Lin, Ayah G Ahmad, Ken Goldberg (Univerisity of California - Berkeley); Eugen Solowjow (Siemens)

8. Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms, by Hanzhe Teng, Yipeng Wang, Xiao'ao Song, Konstantinos Karydis (University of California - Riverside)

• Deadline to submit extended abstract for poster and/or demo:  Aug 25, 2023 (AoE)

• Notification of acceptance:  Sep 8, 2023

• Camera-ready posters:  Sep 25, 2023 (AoE)

• Workshop:  Oct 5, 2023