- Research on the energy independence and quality of operations carried out using robotic technologies in the cultivation of crops and equipment in a universal agricultural robot
- Exploring the capabilities of artificial intelligence to determine the accuracy and coordination of an agricultural robot in positioning and movement through a navigation system and digital vision
- Development of advanced technologies for monitoring soil and crop parameters
- Exploring the possibilities of Internet of Things (IoT) technology to implement and optimize data exchange between the agricultural robot and a server station through a field communication network for data transfer
Increasing the planet’s population poses a serious problem with its nutrition. Agriculture is the sector responsible for this task. One way to tackle this problem is to find new ways to improve the efficiency of agriculture. A major problem is the provision of labor. In countries where this is difficult, production is more expensive than the cost of hiring workers. However, in these countries there is a high production yield and a tendency to automate work processes. Automation can take place both during the entire period of crop cultivation and in the harvesting and storage of production.
The use of robots in agriculture is not a new idea. There are developments in agricultural machinery without human intervention, but they can take on the complex real world with all modern technology. Therefore, these machines are used in agriculture with great success. The current understanding is to create intelligent machines that are capable of making independent decisions and operating in the natural environment without taking over the human control functions. At the same time, these machines must be capable of operating for an extended period of time without supervision.
There is a wide range of technologies that are used in robots and lead to the possibility of a rapid transition of Industry 4.0 to enter the agricultural activity through robotics. Some technologies will need to be developed specifically for agriculture, while other technologies have already been developed for other areas can be adapted to the agricultural domain, such as autonomous vehicles, artificial intelligence and machine vision. Here, however, it is necessary to use the different capabilities and current state of various enabling technologies from hardware to software, multi-robot systems and humanrobot inteligents systems.
Our main goal is to provide an innovative solution to support farmers in order to optimize the working processes and reduce the influence of the human factor on Bulgarian farms. The modern development of IoT and the entry of Industry 4.0 into the agricultural sector should help simplify and diagnose individual diseases and carry out the necessary operations with a minimum of means.
Different models of application will be developed in the forecasting and management of farm processes. A model of the aquatic state of plants will be created and no irrigation regime of tomatoes will be predicted for precise irrigation. A system for the study and collection of microclimate data in vegetable cultivation will also be developed.
On the other hand, at the current rate of development of climate change, snow cover has decreased in recent years, which negatively affects crops. The assessment of the snow cover and snow water equivalent is an important parameter for agroproteics.
Plant production is an area where activities and efficiency directly depend on the current and correct data on the state of the environment, the crops grown and the work of the service equipment. The monitoring and analysis process is key to achieving optimal results. In this context, the development of such a local field network of IoT will increase communication between the ground or air equipment implementing units with which data is collected and the server through which artificial intelligence communicates between the different units and monitors the correct execution of operations.
SCIENTIFIC TASKS:
1.1.1. Research on the energy independence and quality of operations carried out using robotic technologies in the cultivation of crops and equipment in a universal agricultural robot
ACTIVITIES
• Design of an agricultural robot.
• Production and functional tests of an agricultural robot.
• Study of the resistance of an agricultural robot when moving in polish conditions.
• Study of the energy independence of an agricultural robot when carrying out work operations.
• Examination of the quality of the work operations carried out.
1.1.2. Exploring the capabilities of artificial intelligence to determine the accuracy and coordination of an agricultural robot in positioning and movement through a navigation system and digital vision.
ACTIVITIES
• Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot navigation system.
• Study of the accuracy of an agrorobot in determining its location by using different GSCI (NAVSTAR-USA, GLONASS-Russia, GALILEO-EU) or in their joint use.
• Development of a methodology for determining the space-time characteristics of constellations of navigation satellites and their accessibility when sharing the NAVSTAR-USA, GLONASS-Russia, GALILEO-EU GSCI.
• Develop a 3D model of the area (field) using drone-orthophotogrametry technology and visualization of the agrorobot according to its GPS data.
• Installation of the elements of digital vision of the robot.
• Coordination and optimization of the movement of the robot to the resulting position by working together on the navigation system, the map from the locality model and the images from the digital vision of the robot.
• Develop an algorithm to create a computer program to select a turning trajectory and generate a turning strip when moving an autonomous agricultural ro• Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot na• Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot navigation system.
• Study of the accuracy of an agrorobot in determining its location by using different GSCI (NAVSTAR-USA, GLONASS-Russia, GALILEO-EU) or in their joint use.
• Development of a methodology for determining the space-time characteristics of constellations of navigation satellites and their accessibility when sharing the NAVSTAR-USA, GLONASS-Russia, GALILEO-EU GSCI.
• Develop a 3D model of the area (field) using drone-orthophotogrametry technology and visualization of the agrorobot according to its GPS data.
• Installation of the elements of digital vision of the robot.
• Coordination and optimization of the movement of the robot to the resulting position by working together on the navigation system, the map from the locality model and the images from the digital vision of the robot.
• Develop an algorithm to create a computer program to select a turning trajectory and generate a turning strip when moving an autonomous agricultural ro• Integration of a global satellite radio navigation system (GSRS) GALILEO receiver to the agrorobot navigation system.
• Study of the accuracy of an agrorobot in determining its location by using different GSCI (NAVSTAR-USA, GLONASS-Russia, GALILEO-EU) or in their joint use.
• Development of a methodology for determining the space-time characteristics of constellations of navigation satellites and their accessibility when sharing the NAVSTAR-USA, GLONASS-Russia, GALILEO-EU GSCI.
• Develop a 3D model of the area (field) using drone-orthophotogrametry technology and visualization of the agrorobot according to its GPS data.
• Installation of the elements of digital vision of the robot.
• Coordination and optimization of the movement of the robot to the resulting position by working together on the navigation system, the map from the locality model and the images from the digital vision of the robot.
• Develop an algorithm to create a computer program to select a turning trajectory and generate a turning strip when moving an autonomous agricultural robot in an irregularly shaped field.
• Design and modeling of an autonomous system with increased accuracy and ground station for the management of a coaxial helicopter for agricultural purposes.
Develop machine learning algorithms that are based on information from large databases that are derived from the digital vision of the helicopter for agricultural purposes.
• Create a protocol for collecting and analyzing a large amount of data for the detection of plant pests through the digital vision of the helicopter for agricultural purposes.
• Monitoring the quality of the operations performed through the digital vision of the robot and helicopter.
1.1.3. Development of advanced technologies for monitoring soil and crop parameters.
ACTIVITIES
• Development of a methodology for examining the relationship between the color of the leaves of greenhouse tomato plantations (and other greenhouse vegetables) and microclimatic parameters (soil moisture and temperature).
• Research and selection of digital color components under different quality factors in greenhouse tomato plantations (before/after watering, young/old leaves).
• Create digital models using standard statistical methods using data mining and mashine learning algorithms in greenhouse tomato plantations.
• Forecasting soil moisture (the need for watering) based on leaf color, soil temperature and quality factors (based on models created) when growing greenhouse tomatoes.
• Development of an alternative methodology for remote monitoring of the microclimate in Polish tomato production.
• Remote monitoring of the microclimate in Polish tomato production through the various phenophases and the manifestation of diseases.
• Modeling of snow coating parameters.
• Analysis of the snow coating relationship (Globsnow) and crop development through satellite measurements of the Finnish Space Agency.
• Analysis of calculated snow water equivalent, snow cover and duration with the developed model using satellite data of the Copernicus Land Monitoring Services program.
1.1.4. Exploring the possibilities of Internet of Things (IoT) technology to implement and optimize data exchange between the agricultural robot and a server station through a field communication network for data transfer.
ACTIVITIES
• Create a local field IoT (2.4-5 GHz Wi-Fi, Lora-Wan, Zig-Bee) network to provide robot-server communication.
• Create a protocol to optimize data transfer to the server.
• Create a database of data records from all sensors installed on the agrorobot.
| Package Manager | Assoc. Prof. PhD. eng. Georgi Komitov | gkomitov@au-plovdiv.bg | |
| Членове на научния колектив | Prof. PhD. eng. Miroslav Tsvetkov | ||
| Prof. PhD. eng. Chavdar Alexandrov | |||
| Prof. DTS. eng. Rosen Ivanov | |||
| Assoc. Prof. PhD. eng. Nikolai Zlatov | |||
| Assoc. Prof. PhD. eng. Valentin Penev | |||
| Assoc. Prof. PhD. Atanas Sevov | |||
| Assoc. Prof. PhD. eng. Vladimir Kotev | |||
| Assoc. Prof. PhD. eng. Jordan Sivkov | |||
| Assoc. Prof. PhD. eng. Zhulieta Arnaudova | |||
| Assoc. Prof. PhD. Velika Kuneva | |||
| Assoc. Prof. PhD. eng. Donka Ivanova | |||
| Assoc. Prof. PhD. eng. Tanya Pehlivanova | |||
| Assoc. Prof. PhD. eng. Krasimir Trendafilov | |||
| Assoc. Prof. PhD. Olga Nicheva | |||
| Assoc. Prof. PhD. Polya Dobreva | |||
| Assoc. Prof. PhD. eng. Sergey Ranchev | |||
| Chief Assist. PhD. eng. Ivan Mitkov | |||
| Chief Assist. PhD. eng. Manol Dallev | |||
| Chief Assist. PhD. eng. Vera Stefanova | |||
| Chief Assist. PhD. Dimitar Razpopov | |||
| Chief Assist. PhD. eng. Georgi Kadikyarov | |||
| Chief Assist. PhD. eng. Gergana Staneva | |||
| Chief Assist. PhD. eng. Galin Tihanov | |||
| Assist. eng. Veselin Atanasov | |||
| PhD student eng. Georgi Ivanov | |||
| PhD student eng. Svetoslav Atanasov | |||
| PhD student Georgi Stanchev | |||
| eng. Georgi Georgiev | |||
| eng. Gari Roulands | |||
| Student Dobri Dobrev | |||
| Student Petko Petkov | |||
| Student Hristo Asanski | |||
| Student Angel Pavlov | |||
| Student Iliyan Iliev | |||