Robotics in Agriculture and Forestry

  • Marcel BergermanEmail author
  • John Billingsley
  • John Reid
  • Eldert van Henten
Part of the Springer Handbooks book series (SHB)


Robotics for agriculture and forestry (A&F ) represents the ultimate application of one of our society’s latest and most advanced innovations to its most ancient and important industries. Over the course of history, mechanization and automation increased crop output several orders of magnitude, enabling a geometric growth in population and an increase in quality of life across the globe. Rapid population growth and rising incomes in developing countries, however, require ever larger amounts of A&F output. This chapter addresses robotics for A&F in the form of case studies where robotics is being successfully applied to solve well-identified problems. With respect to plant crops, the focus is on the in-field or in-farm tasks necessary to guarantee a quality crop and, generally speaking, end at harvest time. In the livestock domain, the focus is on breeding and nurturing, exploiting, harvesting, and slaughtering and processing. The chapter is organized in four main sections. The first one explains the scope, in particular, what aspects of robotics for A&F are dealt with in the chapter. The second one discusses the challenges and opportunities associated with the application of robotics to A&F. The third section is the core of the chapter, presenting twenty case studies that showcase (mostly) mature applications of robotics in various agricultural and forestry domains. The case studies are not meant to be comprehensive but instead to give the reader a general overview of how robotics has been applied to A&F in the last 10 years. The fourth section concludes the chapter with a discussion on specific improvements to current technology and paths to commercialization.


Total Factor Productivity Unmanned Aerial Vehicle Precision Agriculture Laser Rangefinder Protected Cultivation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.







agriculture and forestry


charge-coupled device


degree of freedom


gardening with a cognitive system


global navigation satellite system


global positioning system


human–machine interaction


nursery and greenhouse


national livestock identification scheme


optimal coverage path planning




pulse-width modulation


real-time kinematics


simultaneous localization and mapping


total factor productivity




unmanned aerial vehicle


weighted difference vegetation index


wireless sensor network


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Marcel Bergerman
    • 1
    Email author
  • John Billingsley
    • 2
  • John Reid
    • 3
  • Eldert van Henten
    • 4
  1. 1.Robotics InstituteCarnegie Mellon UniversityPittsburghUSA
  2. 2.Faculty of Engineering and SurveyingUniversity of Southern QueenslandToowoombaAustralia
  3. 3.Moline Technology Innovation CenterJohn Deere Co.MolineUSA
  4. 4.Wageningen UR Greenhouse HorticultureWageningen UniversityWageningenNetherlands

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