S. Kallweit et al.: Recent Developments in Agricultural Robotics


Bio Information

Stephan Kallweit is Professor at the MASCOR Institute/Mobile Autonomous Systems and Cognitive Robotics at FH Aachen University of Applied Sciences.

University Education

  • Studies Dipl.-Ing. in Mechanical Engineering, Turbomachinery and Hydraulics, TU Berlin, April 1985 – October 1991, (Grade: Very Good)
  • Academic Grade January 1995, Dr.-Ing., Dissertation: „Investigation of Knowledge based Systems for Diagnoses of Hydraulic Turbomachinery“, (Grade: Summa cum Laude)
  • Main Topics Automation, Artificial Intelligence, Neural Networks, Fluid Mechanics, Turbomachinery, Laser Optical Measuring Techniques

Work Experience

  • October 1991 – February 1992 Project Engineer at Gier&Partner Industrieanlagen GmbH
  • March 1992 – January 1995 Research Fellow at TU Berlin „Institut für Hydraulische Strömungs-maschinen“ (Hydraulic Turbomachinery) Prof. Dr.-Ing. H. Siekmann, Work for DFG Research Project „Inducer“, KSB Research Project „Investigation of dynamic Operating Parameters for the Automation of Pump stations“
  • March 1995 Managing Director of ILA GmbH Jülich, Head of Technical Development and Sales for Laser Optical Flow Measurement Tech-niques (LDV, PIV and LiF)
  • Since April 2011 Professor at the University of Applied Sciences Aachen for Automation Technology and Robotics, Department of Mechanical Engineering and Mechatronics, Founder Member of the Institute for Mobile Autonomous Systems and Cognitive Robotics (MASCOR) at FH Aachen, Founder Member of IaAM (Institute for Applied Automation and Mechatronics), FH Aachen

Research Topics

  • Robotics Autonomous Mobile Systems, UAV Technology, Robot based Assembly, Humanoid Robotics, Collaborating Systems, Maintenance Robots for Wind Turbines, Agricultural Robotics
  • Digital Image Processing 3D-Reconstruction, Stereo-Vision, Correlation based Image Processing, High-Power-LEDs, Tracking Systems, Structured Light, Neural Networks (DCNN), Hardware Acceleration
  • Measuring Techniques LIDAR, Laser Doppler and Particle Image Velocimetry, mmWave RADAR
  • Robotics Competitions Finalist at MBZIRC 2017 and 2020, Participant of Grand Challenge 2017 and 2020

Presentation Abstract

Autonomous mobile systems are used in a variety of applications. Mobile Robotics is one of the most promising future technologies supported by Open Source Hard- and Software resources. The amount of agricultural applications in field robotics are constantly increasing: precision farming, weed control and harvesting are only a couple of possible use cases for robots. These use cases are supported by the progress in sensor technology like e.g. affordable LiDAR systems, machine learning e.g. DCNN for image classification, electric mobility and Open Source software solutions e.g. the Robot Operating System (ROS).

Our talk contributes to all these vibrant technologies and combine them, generating an agricultural robot: the ETAROB. Starting just a couple of years ago, the team developed a new robotic platform which supports agricultural applications, like selective non-chemical weeding, precision spraying, sowing and autonomous harvesting.    

Authors: Stephan Kallweit, Josef Franko, Heiko Engemann and Enno Duelberg


Video

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