Spread Spectrum Sound with TDMA and INS Hybrid Navigation System for Indoor Environment

Indoor navigation plays an essential role in agricultural robots that operate in greenhouses. One of the most effective methods for indoor navigation is the spread spectrum sound (SS-sound) system. In this system, the time of arrival (ToA) of the spread spectrum modulated sound is used for localization. However, there is a near-far problem. Transmitting the SS-sound from multiple anchors using time division multiple access (TDMA) is adequate to solve the near-far problem. However, localization is impossible because the ToA from multiple anchors cannot be simultaneously acquired. To solve this problem, a method for combining the SS-sound system with TDMA and an inertial navigation system is proposed in this study. The effectiveness of the proposed method was demonstrated through numerical simulations of a ground robot and experimentally using a crawler robot.

Control System of a Robotic Irrigation Machine Based on the Mamdani Fuzzy Algorithm

The article analyzes the tasks that can be solved by agricultural robots. The purpose of the study was the robotization of the "Fregat" type crop irrigation machine by the fuzzy control of irrigation technological processes, which allows to control the irrigation rate. It is proposed to use in a robotic irrigation machine the analog valve-setter of the speed of the last cart, powered by electricity. It is recommended to include a diagnostic subsystem in the fuzzy control system of the flow control valve, which includes sensors for measuring the soil moisture and the slope of the irrigation machine in various areas of the field. The mathematical model of fuzzy control of the irrigation machine is developed based on the software control of the water supply depending on the terrain of the field, the speed of irrigation machine and soil moisture to reduce water consumption and improve the efficiency and quality of irrigation. The Mamdani algorithm, which is implemented in the MATLAB package, is proposed as a fuzzy inference system. The formalization of the description of the indicators of the irrigation machine is carried out by specifying linguistic variables. The proposed mathematical model can be used in the design of control systems for other robotic agricultural machines.

Development of Monitoring Robot System for Tomato Fruits in Hydroponic Greenhouses

Crop monitoring is highly important in terms of the efficient and stable performance of tasks such as planting, spraying, and harvesting, and for this reason, several studies are being conducted to develop and improve crop monitoring robots. In addition, the applications of deep learning algorithms are increasing in the development of agricultural robots since deep learning algorithms that use convolutional neural networks have been proven to show outstanding performance in image classification, segmentation, and object detection. However, most of these applications are focused on the development of harvesting robots, and thus, there are only a few studies that improve and develop monitoring robots through the use of deep learning. For this reason, we aimed to develop a real-time robot monitoring system for the generative growth of tomatoes. The presented method detects tomato fruits grown in hydroponic greenhouses using the Faster R-CNN (region-based convolutional neural network). In addition, we sought to select a color model that was robust to external light, and we used hue values to develop an image-based maturity standard for tomato fruits; furthermore, the developed maturity standard was verified through comparison with expert classification. Finally, the number of tomatoes was counted using a centroid-based tracking algorithm. We trained the detection model using an open dataset and tested the whole system in real-time in a hydroponic greenhouse. A total of 53 tomato fruits were used to verify the developed system, and the developed system achieved 88.6% detection accuracy when completely obscured fruits not captured by the camera were included. When excluding obscured fruits, the system’s accuracy was 90.2%. For the maturity classification, we conducted qualitative evaluations with the assistance of experts.

Application of the Altshuler's algorithm for determining the overall dimensions of an agrorobot

Modern robots perform a number of comprehensive tasks. In the agricultural sector, they are able to work on large areas with a wide range of crops with different agronomic requirements. They are highly maneuverable, some of them have the ability to rotate around its axis (can work in hard to reach places and small terrains). In the beginning, agricultural robots were slow, light and small. At the same time, they could not fully meet the requirements of their „employers“ due to the comprehensiveness of agricultural activity and the level of development of scientific and technological progress. The tasks of the agrorobots will only increase - from data collection, weeding, performing various agrotechnical activities to offering many functions. The present article uses the famous TRIZ theory, developed by the Soviet inventor Henrik Altshuler. Its basic principle is the resolution of an unresolved contradiction by means of an inventive solution, if any. An unresolved inconsistency occurs if, when one parameter improvement is introduced into a system, another parameter deteriorates. These contradictions are called „technical contradictions“. The overall dimensions of an agricultural robot for growing some crops have been determined.

Determining the energy efficiency of an agrorobot

The problem of feeding the population and the lack of trained staff for growing crops is increasing all over the world. This inevitably leads to a change in technology for growing crops. These new technologies rely on autonomous robotic systems for the continuous cultivation of crops without human personnel. Robots are small, smart, interconnected, lightweight machines that aim to release the person from the basic everyday pursuits. Globally, there is a trend in agriculture to automate the hard manual labor with continued increases in yields to feed the population. This article discusses the problems of determining the main energy aspects of agricultural robots. Guidelines are given for determining the energy saving of the robot, depending on the time for its long autonomous operation, the terrain to be cultivated and a number of other factors. Exemplary values of the energy required to drive the agricultural robot and the time for energy recovery through renewable energy sources have been determined.

Application of Robots and Robotic Systems in Agriculture

The paper depicts agricultural robots that can perform complex tasks. Fast development and application of agricultural robotics is a result of increased development of agricultural machinery. Robots are complex and intelligent systems with a significant role in agriculture that are becoming an integral part of both the technological and scientific progress. The paper presents some important roles of robots and robotic systems in various agricultural areas and explains the deployment of new technologies supported by the examples of their application in arable farming, horticulture, and forestry. Robotics application decreases the deployment of human resources, enables significant production cost savings, and increases production capacity. The application of robotic systems facilitates high precision levels and repetition speed regarding time and space, which cannot be replicated by farmers