Team FarmBeast
Team members
Benjamin Založnik, Emil Maltar, Jaša Jernej Rakun Kokalj, Luka Kramolc, Matija Slapšak, Matic Presečnik, Niko Korošec, Oscar Fernando Hernandez Lopez, Rok Friš,
Žiga Breznikar
Team captain’s name
Jaša Jernej Rakun Kokalj
Instructor(s)
Prof. Miran Lakota, Chair of Biosystems Engineering, Faculty of Agriculture and Life Sciences, University of Maribor, Hoče, Slovenia.
Dr. Jurij Rakun, Chair of Biosystems Engineering, Faculty of Agriculture and Life Sciences, University of Maribor, Hoče, Slovenia.
Dr. Mitja Truntič, Laboratory for Power Electronics, Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.
Participating in the FRE since
2008, except 2017
Description of the team and robot
FarmBeast is an interdisciplinary educational and research initiative at the University of Maribor focused on autonomous robotic systems for precision agriculture. The project connects students and researchers from agriculture, computer science, electrical engineering and mechanical engineering, enabling hands‒on development of AI‒based sensing, navigation and robotic manipulation technologies. FarmBeast supports practical learning, innovation and applied research in smart farming and agricultural robotics.
In recent years, the project has been led by the Faculty of Agriculture and Life Sciences, University of Maribor in close cooperation with the Faculty of Mechanical Engineering, University of Maribor and the Faculty of Electrical Engineering and Computer Science, University of Maribor.
Robot specifications
W x L x H (cm):
99 x 50 x 51
Weight (kg):
80
Commercial or prototype:
Prototype
Total no. of wheels / no. driven wheels:
4
Drivetrain concept/ max. speed (m/s):
3
Turning radius (cm):
0
Battery type / capacity (Ah):
12
Total motor power (W):
800
No. of sensors internal/
external:
Sensor type:
Velodyne VLP-16 multichannel LIDAR ||SICK TIM310 LIDAR sensor,2 x RGBD camera, IMU (Xsens)
Controller system software description:
Linux Ubuntu, Robot Operating System
Controller system hardware description:
Raspberry Pi 4 Model B (low level computer)
Intel NUC 7i7BNH (high level computer)
Short strategy description for navigation and applications:
Custom infield navigation algorithm based on Velodyne / Intel Realsense RGB(D) and IMU readings.
These are the commercial team sponsors & partners:
SMTd.o.o, CLAAS, EMSISO d.o.o, Tuli d.o.o, IHS d.o.o, AzureFIlm d.o.o, ODrive Robotics, Inc., Rehar d.o.o.