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This paper aims to investigate if a Cartesian robot system for kiwifruit harvesting works more effectively and efficiently than an articulated robot system. The robot is a key component in agricultural automation. For instance, multiple robot arm system has been developed for kiwifruit harvesting recently because of the significant labor shortage issue. The industrial robots for factory automation usually have articulated configuration which is suitable for the tasks in the manufacturing and production environment. However, this articulated configuration may not fit for agricultural application due to the large outdoor environment.

The kiwifruit harvesting tasks are completed step by step so that the robot workspace covers the canopy completely. A two-arm, Cartesian kiwifruit harvesting robot system and several field experiments are developed for the investigation. The harvest cycle time of the Cartesian robot system is compared to that of an articulated robot system. The difference is analyzed based on the workspace geometries of these two robot configurations.

It is found that the kiwifruit harvesting productivity is increased by using a multiple robot system with Cartesian configuration owing to its regular workspace geometry.

An articulated robot is a common configuration for manufacturing because of its simple structure and the relatively static factory environment. Most of the agricultural robotics research studies use single articulated robot for their implementation. This paper pinpoints how the workspace of a multiple robot system affects the harvest cycle time for kiwifruit harvesting in a pergola style kiwifruit orchard.

A harvesting robot is developed as part of kiwifruit industry automation in New Zealand. This kiwifruit harvester is currently not economically viable, as it drops and damages too many kiwifruit in the harvesting task due to the positional inaccuracy of the gripper. This is due to the difficulties in measuring the exact effective dimensions of the gripper from the manipulator. The purpose of this study is to obtain the effective gripper dimensions using kinematic calibration procedures.

A setup of a constraint plate with a dial gauge is proposed to acquire the calibration data. The constraint plate is positioned above the robot. The data is obtained by using a dial gauge and a permanent marker. The effective dimensions of the gripper are used as error parameters in the calibration process. Calibration is exercised by minimizing the difference between target positions and measured positions iteratively.

The robot with the obtained effective dimensions is tested in the field. It is found that the fruit drops due to positional inaccuracy of the gripper are greatly reduced after calibration.

The kiwifruit industry in New Zealand is growing rapidly and announced plans in 2017 to double global sales by 2025. This growth will put extra pressure on the labour supply for harvesting. Furthermore, the Covid pandemic and resulting border restrictions have dramatically reduced seasonal imported labour availability. A robotic system is a potential solution to address the labour shortages for harvesting kiwifruit.

For kiwifruit harvesting, the picking envelope is well above the robot; the experimental data points obtained by placing a constraint plate above the robot are at similar positions to the target positions of kiwifruit. Using this set of data points for calibration yields a good effect of obtaining the effective dimension of the gripper, which reduces the positional inaccuracy as shown in the field test results.

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 recent fruit picking robot developments with an emphasis on corporate activity rather than academic research. It also aims to provide a view on the commercial prospects for these developments.

Following a short introduction, this first discusses strawberry and other soft fruit picking robot developments conducted principally by commercial organisations. It then provides similar details of robots for harvesting apples and other hard fruits. This is followed by a discussion and concluding comments.

The shortage of seasonal fruit pickers has stimulated the need for automation. Accordingly, a growing community of companies, many founded in the past five years, are developing fruit picking robots. These are aimed at both soft and hard fruits, such as strawberries and apples, respectively, and exploit advanced vision systems, image processing techniques and AI. Some products are already on the market, whereas many more are due for commercial release during the next two years into what is expected to be a highly competitive market.

This provides details of the emerging fruit picking robot business by describing the products and manufacturing companies.

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.

Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles.

To make the length of each pixel equal, the image is restored to the aerial view in the world coordinate system. To solve the problem of too much calculation caused by too many particles, a certain number of particles are scattered near the crop boundary and the distribution regularities of particles’ weight are analyzed. Based on the analysis, a novel boundary positioning method is presented. In the meantime, to improve the robustness of the algorithm, the back-projection algorithm is also used for boundary positioning.

Experiments demonstrate that the proposed method could well meet the precision and real-time requirements with the measurement error within 55 mm.

In visual target tracking, using particle filtering, a rectangular is used to track the target and cannot obtain the boundary information. This paper studied the distribution of the particle set near the crop boundary and proposed an improved particle filtering algorithm. In the algorithm, a small amount of particles is used to determine the crop boundary and accurate positioning of the crop boundary is realized.

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.

SILVER, the special interest group on advanced robotics and intelligent automation, is holding a series of meetings on applications in different sectors of industry. The May meeting was held at the Silsoe Research Institute in Bedfordshire. Speakers from Silsoe, as well as from universities and industry, reviewed a number of applications, current and potential, and some systems were demonstrated during the lunch break.

The purpose of this paper is to review the use of robots in the Japanese food industry, today and tomorrow.

This paper is based on research papers, exhibitions, press releases and interviews.

The paper finds that food palletizing and packaging are the popular applications at present. Food processing and handling are emerging. Agricultural and farming applications are yet to come in spite of intensive on‐going R&D efforts.

This paper presents issues to overcome for the robotization of the industry in the future.

This paper seeks to report on the Robot Award of Japan and to review the award winners of 2010.

The paper is based on findings at the exhibition, published papers and in‐depth interviews with award winners.

The Ministry of Economics, Trade and Industry of Japanese Government is trying to create a new robotic business and the industry and academia is responding to it.

The paper reviews the direction of Japan's robot business.

The paper focuses on commercial success and potentials rather than academic value or intriguing technology.