Max Robotics — Global Service Robot Directory + US Certification

About

Karsten Bohlmann’s research lies at the intersection of agricultural robotics, autonomous navigation, and environmental perception. His most impactful work, “Plant Species Classification Using a 3D LIDAR Sensor and Machine Learning” (64 citations), pioneered the use of 3D LIDAR for robust plant identification—a critical enabler for precision weed control and crop scouting. He further advanced outdoor robot perception through terrain classification studies that compared local feature methods like Local Binary Patterns (31 citations) and demonstrated how 3D LIDAR and camera fusion can maintain classification accuracy under varying lighting conditions (39 citations). Bohlmann also contributed to autonomous human-robot collaboration with a system for person-following in outdoor environments using 3D LIDAR, and developed automated odometry self-calibration techniques for four-wheel-steering robots. His work on integrating geographical data with sonar to improve GPS localization for mobile robots rounds out a career focused on making field robots more perceptive, reliable, and autonomous. Through these contributions, Bohlmann has helped lay the groundwork for practical agricultural robotics and robust outdoor navigation.