Reprint

Robots and Autonomous Machines for Agriculture Production

Edited by
August 2023
520 pages
  • ISBN978-3-0365-8376-1 (Hardback)
  • ISBN978-3-0365-8377-8 (PDF)

This book is a reprint of the Special Issue Robots and Autonomous Machines for Agriculture Production that was published in

Biology & Life Sciences
Engineering
Environmental & Earth Sciences
Summary

Global population growth, population aging, declining labor force levels, and rising production costs pose more challenges to agricultural production. In recent years, due to the improved performance of artificial intelligence, precision agriculture, and advanced control, they have been widely used in various agricultural applications, including management, disease detection, crop monitoring, yield estimation, and crop harvesting. Robotics and autonomous machines represent a high-level application of automation in agriculture, based on precise and resource-efficient approaches to sustainably achieve greater efficiency and quality in the production of agricultural products while reducing environmental impact. Reactive technologies based on agricultural robots and autonomous machines are separate but closely related fields covering the application of automated control and robotic platforms at all levels of agricultural production. In robotic or autonomous systems, agricultural sensing and control is particularly difficult due to the complexity of the environment in which agricultural production operates. The open robot system has good expansibility, versatility and flexible operation ability. The establishment of agricultural robot control system can guarantee the reliability and real-time control. A total of 26 papers are included that explores the various ways in which robotics and autonomous machines for agricultural production address general problems.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
mobile manipulation; optimization and optimal control; agricultural robotics; viticulture; jujube pruning; manipulator; kinematic analysis; high-speed photography technology; performance test; picking manipulator; motion planning; TO-RRT; step-size dichotomy; regression superposition; robotic pest control; Mask R-CNN; skeleton extraction; binocular vision; stereo matching; machine vision; picking robot; apple detection; YOLOX; ShufflenetV2; point cloud registration of fruit trees; lightning attachment procedure optimization; density-based spatial clustering of applications with noise; information perception of fruit trees; precision planter; motor-driven; CANopen protocol; photoelectric sensor; no-tillage; straw-rotting fungus; multiarm harvesting trajectory optimization; multiobjective optimization; cluster fruit; genetic ant colony stepwise algorithm; dairy farm; pusher robot; path extraction; obstacle avoidance; high-performance film for full recycling; film recycling; field experiment; film recycling rate; precision agriculture; Industry 4.0; technology; adoption; unmanned vehicles; smart production; drones; robots; cotton precision planter; cotton seeds; broadcast monitoring; missed broadcast monitoring; sowing quality; electrical characteristics; poultry eggs; nondestructive detection; cracked eggs; machine learning; garlic seeding; orientation recognition; garlic clove righting; deep learning; fully connected neural network; autonomous navigation; navigation line extraction; orchard machinery; deep learning; least-square; apple harvesting; soft gripper; Fin Ray effect; finite element analysis; constant-pressure feedback; slip detection; fresh weight prediction; growth model; naive Bayesian network; solar greenhouse; substrate-cultivated lettuce; phenotyping; agricultural robot; tiller counting; deep learning; residual network; agriculture; path planning; neighborhood collection; autonomous vehicle; genetic algorithm; global optimization; bale collection problem; forage handling; pineapple eye; three-dimensional; YOLOv5; stereo-matching; cotton seeder; duckbill; Simufact Welding; welding robot; automated welding; apple grader; YOLOv5; attention mechanism SE; DIoU_Loss; mish; autonomous robots; agriculture; data acquisition; computer vision; shrimp; automatic peeling machines; tactile perception; recognition; nondestructive detection; poultry eggs; wavelet scattering convolutional network; microcurrent signal analysis; egg’s electrical characteristic model; precision agriculture; autonomous robots; artificial intelligence; IoT; cloud computing; n/a