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Trends in Agricultural Robots. A Comparative Agronomic Grid Based on a French Overview

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Equipment innovation is one of the crucial levers for the improvement of economic, societal and environmental performances of agriculture. In particular, precision farming is expected to be among the 10 technologies that could change our lives. Amid the different technologies enabling a greater precision of agriculture, robotics and sensors could radically change the way of farming. Automatic machines collecting and managing data, eventually feeding a bigdata approach, could provide new tools for fine-tuning farmers’ decision making and help them in mastering the environmental footprint of agriculture. Nevertheless, what is a robot from the agricultural point of view? What are the solutions under development or on the market? How to compare them? The disruptive transformation of the agricultural machinery market requires the definition of new landmarks, especially for agronomists who are facing new opportunities and technologies. We present here the early results of a comparative overview realized by a group of students in agronomy and specializing in agricultural equipment and new technologies at UniLaSalle. The five students were asked to provide figures and a summary of the agricultural robots available in France, either on the market or upcoming. Firstly, they defined what a “robot” is. They referred to Coiffet (2007) who considers “robot” a machine for the human assistance executing a work or a physical task, either as a tool handled during the execution of the task or capable to perform the work without human intervention. Accordingly, the database includes only agricultural machines fulfilling at least two out of the three following criteria: the capability to execute a task, the operational flexibility, the self-adaptability to the working environment. Three robot classes were identified (decision, assistance or substitution) further classified in two agricultural domains and related operational subdomains: crop production (including permanent crops, horticulture, field crop and other crops) and breeding (including cattle, poultry, and pig). Out of a 4 months work, the database finally contains 98 robots from 70 enterprises, with full specifications retrieved from more than 300 websites and 7 French agricultural journals, as well as through the participation to some specialized fora. For comparison, the “Agricultural Robots” report by Tractica highlighted 149 profiles over a comparable time period. Drawing upon a solid background in agronomy, the students analysed the farming operation performed by the listed robots, with a focus on the vehicle-soil interface. Altogether, the design and development of this database can provide agronomists with an up-to-date comparative grid of the existing and upcoming agricultural robots. Identifying clear landmarks in the high pace robot landscape will enhance the agronomic evaluation and enable a clearer understanding of robot relevance for farmers.

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Trends in Agricultural Robots. A Comparative Agronomic Grid Based on a French Overview

  1. 1. Trends in Agricultural Robots Davide RIZZO A.HAMEZ F.HENDRYCKS B.VASSEUR B.DETOT A.COMBAUD @pievarino #ChaireAMNT A Comparative Agronomic Grid Based on a French Overview Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  2. 2. UniLaSalle A few words about us, the Chair and the students ©DelphineDIGEON,2017CCBY-SA Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 | ABOUT US | BACKGROUND | DATABASE | RESULTS | CONCLUSION |
  3. 3. Institut Polytechnique UniLaSalle A private higher education institute 2800 students 3 integrated degree programs in Food & Health, Geology & Environment, Agronomy and other Bachelor and Master degree programs 4 Academic and Industrial Chairs 4 research groups and several facilities member of the Lasallian education network 3 campuses in northern France: Beauvais, Rouen, Rennes 3 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  4. 4. 4 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 The Chair is backed by UniLaSalle with the financial support from the Michelin Corporate Foundation, AGCO Massey-Ferguson, the Hauts-de-France Regional Council and the European Regional Development Fund (ERDF). Academic research and education team adressing the innovation of agricultural equipment and technologies We aim to enable students, farmers and producers to master the disruptive transformation of the agricultural machinery and the opportunities provided by new technologies. © Davide Rizzo, 2018 CC BY-NC-SA Rizzo D, Dubois M, Combaud A (2018) Innovation des agroéquipements : au carrefour entre agriculteurs, industriels et formation. Beauvais, FRA, http://bit.ly/2G5dPu9
  5. 5. Agricultural Equipment & New Technologies 5 3 years of Bachelor level Fundamental and applied knowledge: background in agricultural sciences. 2 years of Master level Professionalization: applied programs in agriculture, agronomy and the food industry. www.unilasalle.fr The course of study in agronomy backed by the Chair Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 In 2016 the Chair started a new specialization in agricultural equipment and new technologies (AENT) 1st AENT graduation was composed by 5 students and sons of farmers with a solid background in farming.
  6. 6. Background & challenges The disruptive transformation of the agricultural machinery market requires the definition of new landmarks ©DavideRIZZO,2017CCBY-SA Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 | ABOUT US | BACKGROUND | DATABASE | RESULTS | CONCLUSION |
  7. 7. 7 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 | A very busy farmer Jean-Marc Côté, 1900 1900’s postcard from a series of futuristic pictures by Jean-Marc Côté came to light after Isaac Asimov (1986) in “Futuredays: A Nineteenth Century Vision of the Year 2000”. https://publicdomainreview.org/collections/france-in-the-year-2000-1899-1910/
  8. 8. ©NestaCCBY-NC-SAhttps://www.nesta.org.uk/sites/default/files/future_farms_infographic_precision_agriculture.jpg 8 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  9. 9. The EU innovation perspective 9 Precision agriculture is the only farming related innovation that Europe listed among the technologies which could change our lives. Kurrer C, Tarlton J (eds) (2017) Ten more technologies which could change our lives: in-depth analysis http://bit.ly/Kurrer_2017 Van Woensel L, Archer G (2015) Ten technologies which could change our lives: potential impacts and policy implications. European Commission, Brussels http://bit.ly/2vF5HKp  Autonomous Vehicles  Graphene  3D printing  Massive Open Online Courses  Virtual currencies (Bitcoin)  Wearable technologies  Drones  Aquaponic systems  Smart home technologies  Electricity storage (hydrogen)  Electric cars  Intelligent urban transport systems  Magnetic levitation-based transport  Wood  Precision agriculture  Quantum technologies  Radio frequency identification tags  Big data and health care  Organoids  Genome editing Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  10. 10. CAP encourages digital farming https://ec.europa.eu/info/news/future-cap-whats-cooking-next-cap_en “ The future Common Agricultural Policy will be much more focused on encouraging innovation (for example through identifying where there is a common need that technology might be able to meet) and on helping especially small and medium-sized farms to join the digital farming revolution.” ©xaviergpCCBY-NChttps://flic.kr/p/EYLGYj 10 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  11. 11. The French challenges 11 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Bournigal J-M (2014) Définir ensemble le futur du secteur des agroéquipements http://bit.ly/Bournigal_2014 Bournigal J-M, Houiller F, Lecouvey P, Pringuet P (2015) Agriculture – Innovations 2025 : 30 projets pour une agriculture compétitive & respectueuse de l’environnement. MinAgri, Paris (FRA) http://bit.ly/Bournigal_2015 https://www.fira-agtech.com A national accelerator program to intensify the conception, validation, and dissemination of tomorrow’s robots for agriculture FIRA's an annual forum that aims to create a community that brings change through agricultural innovation. http://bit.ly/2wdytBc Preparing tomorrow’s agriculture implies developing co-design, agricultural robotics and digital agriculture Robotics is expected to involve precise, effective and safe equipment through research, system innovation and tests
  12. 12. AgriLab® open innovation platform The local territorial institutions have invested in the building of AgriLab® to boost the sustainable and open innovation of the agritech sector in the Hauts-de-France region © AgriLab 12 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 http://agrilab.unilasalle.fr/projets Rizzo D et al (in preparation) Identifying the actors’ interactions within an agricultural innovation system towards sustainability. The case of a French cluster for agritech innovation. In: International workshop on System Innovation towards Sustainable Agriculture SISA 3. Riga, Latvia
  13. 13. Boosting farms automation 13 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 https://4d4f.eu/http://www.handsfreehectare.com https://www.agreenculture.net/challenge-centeol-2018 http://bit.ly/2PgceU1 Network of 8 agtech innovative farms http://bit.ly/2KXx0od
  14. 14. AgTech for precision agriculture 14 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Automatic machines collecting and managing data, (feeding big-data) new tools for fine- tuning farmers’ decision making and to master the environmental footprint of agriculture. Amid the different technologies enabling a greater precision of agriculture, robotics and sensors could radically change the way of farming.
  15. 15. Understand to trust 15 https://ec.europa.eu/commission/commissioners/2014- 2019/vestager/announcements/clearing-path-innovation_en https://goo.gl/images/v31SZD Margrethe Vestager, European Commissioner for Competition Web Summit, Lisbon, 7 November 20175 « … more and more, we’re being asked to put our trust not just in other people, but in computers and algorithms. Algorithms most of us don't fully understand. … The biggest challenge to the future of innovation … it's whether that new technology can succeed in winning the public’s trust. » Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  16. 16. The aim of this presentation 16 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Context (sum-up) What is a robot from the agricultural point of view? What are the solutions under development or on the market? How to compare them? Our aim To present an overview realized by a group of students in agronomy and specializing in agricultural equipment and new technologies at UniLaSalle. ©PETROSS,TERRA-MEPP&WEST,CC-BYhttps://flic.kr/p/XavvBA
  17. 17. Creating a database 5 students were asked to provide an overview of the agricultural robots available in France ©MaximeAGNES,2017 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 | ABOUT US | BACKGROUND | DATABASE | RESULTS | CONCLUSION |
  18. 18. The database background 18 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 The five AENT students were asked (2016) to provide a comparative overview of the agricultural robots available in France, either on the market or upcoming. The study ended in 4 months:  not exahustive Relevant feature: it is based on an agronomic point of view. ©DavideRIZZO,SIMA2017CCBY
  19. 19. One of 3 AENT applied projects Project #1 Defining the specifications of an innovative tractor. Project #2 Database of the agricultural robots available in France. Project #3 Designing and prototyping a weeding robot 19 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Agricultural Equipment & New Technologies, 1st semester (2016) ©MaximeAgnes,2017©MehdiJaber,Rob’Olympades2017 Rizzo et al. 2018. A robot from the scratch in 5 months. How agronomy students could master agricultural machinery innovation. IFSA Congress. http://bit.ly/2md2Mqc
  20. 20. What is a “robot”? COIFFET P (2007) Robots industriels: concepts, définitions et classifications. Ed. Techniques Ingénieur Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 20 https://en.wikipedia.org/wiki/R.U.R.#/media/File:Capek_RUR.jpg A scene from “Rossum's Universal Robots“ by Čapek that first popularized the term “robot” A concept originated in the sci-fi literature upon a real artificial human, characterized mainly by a human-like intelligence including will and conscience. The scientific concept explores instead machines to assist humans for the execution of physical tasks either by cooperation or substitution
  21. 21. Step 1: entry criteria Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 21 The scientific concept of robot implies ■ a machine capable to execute a physical task AND at least: ■ being versatile (capable to execute different tasks) AND/OR ■ auto-adaptive to the working environment COIFFET P (2007) Robots industriels: concepts, définitions et classifications. Ed. Techniques Ingénieur
  22. 22. Step 2: type of interaction Assistant robots collaborating with humans to realize a physical task Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 22 The machines fulfilling the scientific robot definition, so included in the database, were further classified in: Decision robots that support human decision-making Substitution robots that replace humans to realizate a physical task Ladybird by the University of Sydney http://bit.ly/2MVfHpy Effibot, CC-BY-SA-4.0 Scailyna, 2016 https://commons.wikimedia.org/wiki/File:Inn orobo_2015_-_Effidence_-_Effi-bot_02.jpg DINO weeding robot by Naïo Technologies, CC-BY 4.0 D. Rizzo, 2017
  23. 23. Step 3: domain of application Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 23 Field crops Horticulture Permanent crops, fruit groves and vineyards Other, such as turf mowers Dairy cattle Poultry Pig Other cattle breeding (beef) Robots for CROPS Robots for ANIMALS Iconsfromhttps://icons8.com/icon/set/world/ios
  24. 24. Sources 1er Forum International de la Robotique Agricole (FIRA, Nov. 2016) 8 exhibitors, ~ 200 participants Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 24 More than 300 websites https://www.slideshare.net/ByMaddyness/maddyinsi ghts-la-transformation-numrique-dans-le-tourisme [MaddyInsights] 50 Startups et Innovations dans l'Agro-Alimentaire 7 agricultural magazines (e.g., France Agricole) Technical specifications issued from the robot datasheets Icons from https://icons8.com/icon/set/world/ios
  25. 25. Results Key outcomes and perspectives ©MehdiJABER,2017 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 | ABOUT US | BACKGROUND | DATABASE | RESULTS | CONCLUSION |
  26. 26. The database interface /1 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 26
  27. 27. The database interface /2 Up to 80 descriptive fields for each entry Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 27
  28. 28. Database structure 28 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Created with MS Access® 2013 80 tables detailing the various features of each machine and of the producers. A. Master table listing the robots B. Robot features: domain (crops or animals), dimensions, way of moving, energy source, etc. C. Primary functions (see after) D. Producer’s profile E. Control mode and security features 96 robots documented in 4 months (October 2016 to January 2017) A C B D E
  29. 29. Step 1: criteria defining “robot” 29 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Field crops A Horticulture B Permanent C Other D Dairy cattle A Cattle breed. B Poultry C Pig D A B C D Both additional criteria were met mainly by crop robots Auto-adaptivity is associated to field crop robots Versatily is an additional criterion for the robots for cattle crop Both Versatility Adaptivity Both Versatility Robot is an autonomous machine versatile and/or auto- adaptive Coiffet 2007 N = 96 55 22 19 animal A B C D A B C D A B C D A B C D
  30. 30. Step 2: type of interaction /1 30 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 111 4 21 21 2 1 1 2 2 1 1420 4 1 8 8 Assistance (3) Substitution (58)Decision (23) Field crops (33) Horticulture (13) Permanent (6) Other (4) Dairy cattle (21) Poultry (3) Pig (1) Cattle (15) 1 Crops (56) D-S (5) A-S (6) N = 96 Animal (40) Iconsfromhttps://icons8.com/icon/set/world/ios (number of robots)
  31. 31. Step 2: type of interaction /2 31 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Crops: evenly distributed, yet more abundant for decision and hybrid Animals: 37 out of 40 substitution robots (34 for cattle breed) Assistance: quite limited, mostly as hybrid with substitution Substitution robots are prevalent: 58 (+12 hybrids) out of 96 Icons from https://icons8.com/icon/set/world/ios
  32. 32. 3 4 6 4 8 7 2 4 3 7 2 4 6 3 4 4 8 1991 1995 1999 2003 2007 2011 2015 Step 3: domain of application project Crops Animals Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 32 N = 93 Year missing for 3 robots “Agricultural Robots” by Tractica reported 149 profiles over a comparable time period. 58% 42% Crop Animal 3412 4 15 21 13 N= 56 N= 40 6 R-Max, Yamaha https://www.yamaha-motor.com.au/products/sky/aerial-systems/rmax Astronaut 4, Lely https://www.lely.com/ie/news/2014/06/23/44-lely-astronaut-milking- robots-manage-dairy-farm/ 96 robots
  33. 33. 5 18 24 7 9 21 3 9 Load transportation Sensor carrier Field works Milking Stable cleaning Feed management Assistance Data collection Functions per domain 33 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Several robots for crop management realise different field works (from weeding to harvest) Multiple solutions for animal management robots are for available for feed pushing or distribution Other robots are emerging for autonomous data management (assistance) and collection N = 96 CROPANIMALBOTH
  34. 34. Conclusion Take-home message ©DavideRIZZO,2017CCBY-SA Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 | ABOUT US | BACKGROUND | DATABASE | RESULTS | CONCLUSION |
  35. 35. From education to innovation 35 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 Final goal: to ease the mastery of technologies that are currently and for the most exogenous to the agricultural sector. The insights gained by designing and developing the database were propedeutic to build a weeding robot Cf. Rizzo D et al (2018) A robot from the scratch in 5 months. How agronomy students could master agricultural machinery innovation. In: Farming systems: facing uncertainties and enhancing opportunities. Chania, GRC, p 11 http://www.ifsa2018.gr/uploads/attachments/52/Theme1_Rizzo.pdf https://youtu.be/BI4xdYHfF-g
  36. 36. Database limits & interest 36 ©CCBYSA,D.Rizzo,Bootcamp2017 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 ©CCBYD.Rizzo,SIA2018 A student work carried out in four months with a national focus and not-exhaustive sources. Its design can provide agronomists with a comparative grid of the agricultural robots
  37. 37. Take-home message «Do I think todays’ farmers need a robot? I think today’s robots need a farmer!» Identifying landmarks in the high pace robot landscape will enhance the agronomic evaluation and enable a clearer understanding of robot relevance for farmers. Rod Karter Cattle farmer, Australia February 2018 ABC Catalyst 2018, Farmer Needs A Robot http://www.abc.net.au/catalyst/stories/4792106.htm https://youtu.be/oxpZ1c7TsPI Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05 37
  38. 38. Thank you! Any question? We acknowledge the fundamental work done by all the 5 students (graduation year 157) who designed and realized the robot database (and the robot H3VR) Name.surname[at]unilasalle.fr @pievarinowww.unilasalle.fr 38 © Maxime Agnes, 2017 Antoine Baptiste Benoît Quentin Florent Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05
  39. 39. Acknowledgements. This work has been supported by Chaire Agro-Machinisme et Nouvelles Technologies, backed by UniLaSalle with the financial support from the Michelin Corporate Foundation, AGCO Massey-Ferguson, the Hauts-de-France Regional Council and the European Regional Development Fund (ERDF). Suggested citation: Rizzo D, Hamez A, Hendrycks F, Vasseur B, Detot B, Combaud A (2018) Trends in Agricultural Robots: a Comparative Agronomic Grid Based on a French Overview. In: Innovative cropping and farming systems for high quality food production systems. Geneva, CH, p PS7.3-05, p 81 http://www.esa-congress- 2018.ch/wp-content/uploads/2018/08/ESA2018_AbstractBook_A4.pdf Copyright: © 2018 Rizzo et al. This is an open access document distributed under the terms of the Creative Commons Attribution License CC-BY-NS-SA 4.0 that permits free use, distribution, and reproduction in any medium, provided the original author and source are credited. The use shall not be for commercial purposes and any derivate must keep the same license as the original. https://creativecommons.org/licenses/by-nc-sa/4.0/ Design and layout: Davide Rizzo, August 2018 39 Trends in Agricultural Robots ● RIZZO et al. 2018 Parallel Session 7.3 Productivity and Efficiency – abstract PS-7.3-05

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