Timo Maiwald

Friedrich-Alexander-Universität Erlangen-Nürnberg

Papers

Total Citations

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About

Timo Maiwald is a researcher at the forefront of integrating radar sensing with mobile robotics, specializing in gesture recognition and person detection. His work addresses the critical challenge of enabling robust human-robot interaction when sensors are in motion—a scenario where traditional static radar approaches fail. Maiwald’s major contribution lies in demonstrating that 60 GHz FMCW and MIMO radar systems, combined with deep learning, can effectively operate on moving platforms. His 2024 paper on gesture recognition for controlling a moving robot (2 citations) pioneers a method to filter out motion-induced noise, allowing a robot to interpret hand commands in real-time. Complementing this, his work on deep learning-based person detection (1 citation) involved creating a custom dataset of 8,000 frames and training a convolutional neural network to reliably detect humans despite environmental clutter from robot movement. By proving that radar can serve as a viable, privacy-preserving alternative to cameras in dynamic settings, Maiwald is paving the way for safer, more intuitive autonomous systems in logistics, service robotics, and human-robot collaboration.