Robotics and Mechatronics for Agriculture by Dan Zhang and Bin Wei

• Process Optimization of Composting Systems
• Overview of Mechatronic Design for a Weed-Management Robotic System
• Robotics for Spatially and Temporally Unstructured Agricultural Environments
• Current and Future Applications of Cost-Effective Smart Cameras in Agriculture
• From Manual Farming to Automatic and Robotic Based Farming—An Introduction
• Cooperative Robotic Systems in Agriculture
• Adaptive Min-max Model Predictive Control for Field Vehicle Guidance in the Presence of Wheel Slip
• Model Reference Adaptive Control for Uncertain
• Dynamical Systems with Unmatched Disturbances: A Command Governor-Based Approach

Preface to Robotics and Mechatronics for Agriculture PDF

Robotics and mechatronics have been used in many areas, one of which is the agricultural industry. Using robotic-based machines in agriculture will become common in the future.

Automatic machines will replace human beings in agriculture and they can greatly help farmers to achieve efficient farming.

This book will focus on robotics and mechatronics that are used in agriculture. The aim of the book is to introduce state-of-the-art technologies in the field of robotics and mechatronics for agriculture in order to further summarize and improve the methodologies on the agricultural robotics.

Advances made in the past decades have been described in this book. We want to thank all the authors for their contributions to the book.

We are also grateful to the publisher for supporting this project and Vijay Primlani for his assistance both with the publishing venture and the editorial details. We hope the readers find this book informative and useful.

This book consists of 8 chapters. Chapter 1 focuses on the function and mechanism of aeration for process optimization.

Chapter 2 discusses key aspects of designing a robotic platform for managing crops in agriculture. In particular, the system considered seeks to address the increasing threat of weed species resistant to the herbicide.

Chapter 3 presents a case study of an automated “field scout” ground platform equipped with the means for both sensing and manipulating its changing environment for the purpose of providing actionable data (including samples of physical field specimens) to a farmer.

Chapter 4 presents a critical and detailed review of the application of simple color cameras to cover different aspects of the agricultural industry.

Chapter 5 presents some existing robotic-based farming machinery, and some main issues in robotic-based farming are also illustrated.

Chapter 6 reviews collaborative multi-agent systems in agricultural applications involving a RA to RA and RA-to-human agent (HA) collaboration.

Common systems’ control architecture and design, tools and middleware, planning and decision execution, cooperation behavior, and communication systems are discussed with recently developed systems for agricultural applications.

Chapter 7 proposes an adaptive and robust model predictive controller to address the problem of wheel slip in field vehicles.

Chapter 8 focuses on model reference adaptive control of dynamical systems with matched system uncertainties but unmatched disturbances.

The proposed control framework has a high potential to guarantee the completion of autonomous seeding, harvesting, and/or row cropping via unmanned ground vehicles, or farm imaging and monitoring via unmanned aerial vehicles with high accuracy.

Finally, the editors want to acknowledge all the friends and colleagues who contributed to this book.

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Author(s): Dan Zhang, Bin Wei

Publisher: CRC Press, Year: 2017

ISBN: 1138702404,9781138702400

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