Mobile Robots for Digital Farming

This book examines the latest achievements in agricultural mobile robots, specifically those that are used for autonomous weed control, field scouting, mowing, and harvesting. The book examines object identification, task planning algorithms, digitalization and optimization of sensors and the challenges in the context of digital farming.

This book provides a complete and comprehensive reference for agricultural mobile robots, covering all aspects of the design process, from sensing and perceiving to planning and acting for practical farming applications.

Mobile Robots for Digital Farming explores topics such as Robot Operating Systems (ROS), dynamic simulation, artificial intelligence, image processing, and machine learning. Additionally, it features multiple case studies from funded projects and real-field trials.

This book will be useful for professors and academics in various engineering disciplines (mechanical, robotics, control, electrical, computer, and agricultural), graduate and undergraduate students, farmers, commercial growers, startups, private companies, consultancy agencies, equipment suppliers, and agricultural policymakers.

Autorentext

Redmond R. Shamshiri is a scientist at the Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) working toward digitization of agriculture for food security. He holds a Ph.D. in agricultural automation with a focus on control systems and dynamics. His research fields include autonomous navigation of agricultural mobile robots, sensor fusion and artificial intelligence for collision avoidance, Teleoperation, wireless systems, and optimization of controlled environment agriculture.

Ibrahim A. Hameed is currently a Professor and the Deputy Head of research and innovation, and the Head of the international master program in simulation and visualization with the Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim, Norway, where he has been an Associate Professor with the Department of ICT and Natural Sciences, since 2015.

Inhalt

Chapter 1- Sensors, Algorithms, and Software for Autonomous Navigation of Agricultural Mobile Robots

Chapter 2- Robot-Assisted Soil Apparent Electrical Conductivity Measurements in Orchards

Chapter 3- Electrical Tractors for Autonomous Farming

Chapter 4- Agricultural Robotics to Revolutionize Farming: Requirements and Challenges

Chapter 5- Toward Optimizing Path Tracking of Agricultural Mobile Robots with Different Steering Mechanisms: A Simulation Framework