Abstract
Estimations of world population growth urgently require improving the efficiency of agricultural processes, as well as improving safety for people and environmental sustainability, which can be opposing characteristics. Industry is pursuing these objectives by developing the concept of the “intelligent factory” (also referred to as the “smart factory”) and, by studying the similarities between industry and agriculture, we can exploit the achievements attained in industry for agriculture. This article focuses on studying those similarities regarding robotics to advance agriculture toward the concept of “intelligent farms” (smart farms). Thus, this article presents some characteristics that agricultural robots should gain from industrial robots to attain the intelligent farm concept regarding robot morphologies and features as well as communication, computing, and data management techniques. The study, restricted to robotics for outdoor farms due to the fact that robotics for greenhouse farms deserves a specific study, reviews different structures for robot manipulators and mobile robots along with the latest techniques used in intelligent factories to advance the characteristics of robotics for future intelligent farms. This article determines similarities, contrasts, and differences between industrial and field robots and identifies some techniques proven in the industry with an extraordinary potential to be used in outdoor farms such as those derived from methods based on artificial intelligence, cyber-physical systems, Internet of Things, Big Data techniques, and cloud computing procedures. Moreover, different types of robots already in use in industry and services are analyzed and their advantages in agriculture reported (parallel, soft, redundant, and dual manipulators) as well as ground and aerial unmanned robots and multi-robot systems.
Highlights
According to the Food and Agriculture Organization (FAO), the world’s human inhabitants are expected to reach 9.6 billion people by 2050
artificial intelligence (AI) already has an intensive use in robotics, in navigation mobile robots [20], and has a potential in factories: quality checking, prediction of failures, of mobile robots [20], and has a potential in factories: quality checking, prediction of failures, predictive maintenance, digital twins, analysis of environmental impact, use of data, etc., which can predictive maintenance, digital twins, analysis of environmental impact, use of data, etc., which can be be used in farms for similar purposes
LASMEA-CEMAGREF (France), This study investigated the possibility of achieving vehicle guiding using a carrier phase differential global positioning system (GPS) as the only sensor
Summary
According to the Food and Agriculture Organization (FAO), the world’s human inhabitants are expected to reach 9.6 billion people by 2050. The precision farming concept, which consists of assembling different methods and techniques to manage variations in the field to increase crop productivity, improve business profitability, and ensure. The precision farming concept, which consists of assembling different methods and techniques to manage variations in the field to increase crop productivity, improve business profitability, and eco-environmental sustainability, has provided some significant solutions. This article analyses similarities, contrasts, and differences found between industrial and field robots and focuses on presenting some characteristics that agricultural robots should inherit from a broad classification of industrial robots (parallel, soft, redundant, and dual manipulators) to achieve the intelligent farm concept considering robot morphologies and features and communication, IoT sensing [11], computing and data management methods [12], and cyber-physical techniques [13].
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