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This paper aims to provide details of a number of recent and significant agricultural robot research and development activities.

Following an introduction, this first provides a brief overview of agricultural robot research. It then discusses a number of specific activities involving robots for precision weed control and fertiliser application. A selection of harvesting robots and allied technological developments is then considered and is followed by concluding comments.

Agricultural robots are the topic of an extensive research and development effort. Several autonomous robots aimed at precision weed control and fertiliser application have reached the pre-production stage. Equally, harvesting robots are at an advanced stage of development. Both classes exploit state-of-the-art machine vision and image processing technologies which are the topic of a major research effort. These developments will contribute to the forecasted rapid growth in the agricultural robot markets during the next decade.

Robots are expected to play a significant role in meeting the ever increasing demand for food, and this paper provides details of some recent agricultural robot research and development activities.

The purpose of this paper is to describe a methodology for characterization of the robot environment to help solve such problem as designing an optimal agricultural robot for a specific agricultural task.

Defining and characterizing a task is a crucial step in the optimization of a task-specific robot. It is especially difficult in the agricultural domain because of the complexity and unstructured nature of the environment. In this research, trees are modeled from orchards and are used as the robot working environment, the geometrical features of an agricultural task are investigated and a method for designing an optimal agricultural robot is developed. Using this method, a simplified characteristic environment, representing the actual environment, is developed and used.

Case studies showing that the optimal robot, which is designed based on the characteristic environment, is similar to the optimal robot, which is designed based on the actual environment (less than 4 per cent error), is presented, while the optimization run time is significantly shorter (up to 22 times) when using the characteristic environment.

This paper proposes a new concept for solving the robot task-based optimization by the analysis of the task environment and characterizing it by a simpler artificial task environment. The methodology decreases the time of the optimal robot design, allowing to take into account more details in an acceptable time.

The purpose of this paper is to provide details of recent developments in agricultural robots with an emphasis of those that address labour shortages and environmental issues.

Following an introduction which highlights some of the challenges facing the agricultural industry, this discusses recent robotic agricultural vehicle developments and the enabling technologies. It then provides examples of terrestrial and airborne robots employed in precision agricultural practices. Finally, brief conclusions are drawn.

Traditional, labour-intensive and environmentally harmful agricultural practices are not sustainable in the long term, and if food supply is to meet future demand, radical changes will be required. Exploiting recent advances in artificial intelligence (AI), agricultural equipment manufacturers are developing robotic vehicles in response to labour shortages. Precision agricultural practices will mitigate many of the detrimental environmental impacts and can also reduce the reliance on manpower. Weeding robots which reduce or eliminate the use of herbicides have been commercialised by a growing number of companies and again exploit AI techniques. Drones equipped with imaging device are playing an increasingly important role by characterising agricultural and crop conditions, thereby allowing highly targeted agrochemical application.

This illustrates how the agricultural industry is adopting robotic technology in response to the need to increased productivity while mitigating the problems of shortages of labour and environmental degradation.

The purpose of this paper is to propose going one step further in the simulation tools related to agriculture by integrating fleets of mobile robots for the execution of precision agriculture techniques. The proposed new simulation environment allows the user to define different mobiles robots and agricultural implements.

With this computational tool, the crop field, the fleet of robots and the different sensors and actuators that are incorporated into each robot can be configured by means of two interfaces: a configuration interface and a graphical interface, which interact with each other.

The system presented in this article unifies two very different areas – robotics and agriculture – to study and evaluate the implementation of precision agriculture techniques in a 3D virtual world. The simulation environment allows the users to represent realistic characteristics from a defined location and to model different variabilities that may affect the task performance accuracy of the fleet of robots.

This simulation environment, the first in incorporating fleets of heterogeneous mobile robots, provides realistic 3D simulations and videos, which grant a good representation and a better understanding of the robot labor in agricultural activities for researchers and engineers from different areas, who could be involved in the design and application of precision agriculture techniques. The environment is available at the internet, which is an added value for its expansion in the agriculture/robotics family.

The purpose of this paper is to describe a generic software framework for development of agricultural and forestry robots. The primary goal is to provide generic high‐level functionality and to encourage distributed and structured programming, thus leading to faster and simplified development of robots. A secondary goal is to investigate the value of several architecture views when describing different software aspects of a robotics system.

The framework is constructed with a hybrid robot architecture, with a static state machine that implements a flow diagram describing each specific robot. Furthermore, generic modules for GUI, resource management, performance monitoring, and error handling are included. The framework is described with logical, development, process, and physical architecture views.

The multiple architecture views provide complementary information that is valuable both during and after the design phase. The framework has been shown to be efficient and time saving when integrating work by several partners in several robotics projects. Although the framework is guided by the specific needs of harvesting agricultural robots, the result is believed to be of general value for development also of other types of robots.

In this paper, the authors present a novel generic framework for development of agricultural and forestry robots. The robot architecture uses a state machine as replacement for the planner commonly found in other hybrid architectures. The framework is described with multiple architecture views.

This paper aims to illustrate the growing importance of agricultural robots by providing details of recent product developments and their applications.

Following a short introduction, this first discusses a range of agricultural applications of drones. It then provides details of a selection of mobile field robots and their applications. Finally, concluding comments are drawn.

Commercially available aerial and terrestrial robots are playing a rapidly growing role in a diversity of agricultural practices. Key capabilities and benefits include detecting crop stress and disease, predicting crop yields, reducing agrochemical use, overcoming manpower shortages and reducing labour costs and facilitating precision agricultural practices such as highly localised pesticide and herbicide application and the replacement of large, heavy agricultural machines by fleets of small, lightweight robots.

This provides a detailed insight into the many ways in which robots are transforming agricultural practices.

The purpose of this paper is to examine the potential of robots to contribute to producing food for the growing global population.

Following an introduction which provides an historical background to agricultural production and strategies, this paper considers today's use of robots in traditional agricultural practices. It then introduces precision farming (PF) concepts and discuses the potential role of robots in PF and cites a number of recent research activities. Finally, conclusions are drawn.

This paper shows that robots have so far played a minor role in traditional agriculture but new families of small, intelligent and autonomous robots could conduct a range of PF tasks. These would boost productivity and also yield economic and environmental benefits and contribute to more sustainable food production practices.

This paper puts forward the case for the use of small, intelligent robots in PF and argues that they could contribute significantly to global food production.

Automatic target recognition in agricultural harvesting robots is characterized by low detection rates and high false alarm rates due to the unstructured nature of both the environment and the objects. To improve detection human‐robot collaboration levels were defined and implemented. The collaboration level is defined as the level of system autonomy or the level at which the human operator (HO) interacts with the system. Experimental results on images taken in the field indicate that collaboration of HO and robot increases detection and reduces the time required for detection.

The purpose of this paper is to develop a methodology for detecting tree trunks for autonomous agricultural applications performed using mobile robots.

The system is constructed by following the principles of Voronoi diagram method which is one of the machine learning algorithms used by the robotics, mechatronics and automation researchers.

To analyze the accuracy and performance and to make verification and evaluation, both simulation and experimental studies are conducted. The results indicate that the tree trunk detection system developed using Voronoi diagram method can be able to detect tree trunks with high precision.

A novel solution technique to detect tree trunks is proposed. The adaptation of Voronoi diagram method in an agricultural (orchard) task is presented.

The motivation for robotics research in the agricultural field has sparked in consequence of the increasing world population and decreasing agricultural labor availability. This paper aims to analyze the state of the art of pruning and harvesting manipulators used in agriculture.

A research was performed on papers that corresponded to specific keywords. Ten papers were selected based on a set of attributes that made them adequate for review.

The pruning manipulators were used in two different scenarios: grapevines and apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for three types of fruits: strawberries, tomatoes and apples. These manipulators revealed that different kinematic configurations are required for different kinds of end-effectors, as some of these tools only require movement in the horizontal axis and others are required to reach the target with a broad range of orientations.

This work serves to reduce the gap in the literature regarding agricultural manipulators and will support new developments of novel solutions related to agricultural robotic grasping and manipulation.