Exploiting Chlorophyll Fluorescense for building robust low-cost Mowing Area Detectors
Image by Nils Rottmann
Abstract
Detecting cost-effectively and accurately the working area for autonomous lawn mowers is key for widespread automation of garden care. Therefore, we propose an active low-cost sensor approach for detecting fluorescence response. The area to be detected is illuminated by an LED and the chlorophyll fluorescence response is observed by a phototransistor. The signal from the phototransistor is further processed by a transimpedance amplifier, an amplifier and a band pass filter and forwarded to a microprocessor. By choosing only low-cost consumer products for construction, high-volume lowest cost sensors can be built. We demonstrate the feasibility of our low-cost approach by evaluating the sensor mounted on an autonomous lawn mower in a garden environment.
Video of the presentation, Corresponding publication
Nils Rottmann
Team Lead for Robotics & Autonomous Systems
With September 2021, Nils Rottmann started as a Software Developer/Product Owner at the Hako GmbH. He studied Theoretical Mechanical Engineering at the Hamburg University of Technology, Germany and holds a PhD in Robotics from the University of Luebeck, Germany, In his PhD with the title “Smart Sensor, Navigation and Learning Strategies for low-cost lawn care Systems”, he developed low-cost sensor systems and investigated probabilistic learning and modeling approaches. Currenlty, he works as a Team Lead for the robotic section at the Hako GmbH.