Dominik Schindler

Papers

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About

Dominik Schindler is a robotics researcher whose work centers on state estimation, sensor fusion, and autonomous systems for unique robotic platforms. His most influential contribution, the 2013 paper "Unified state estimation for a ballbot," has garnered 30 citations and introduces a novel extended Kalman filter framework that integrates a complete kinematic model with multi-source sensory data. This work enables a ballbot—a robot balancing on a single sphere—to achieve accurate and stable state estimation, a critical challenge in dynamic balancing and control. Schindler further demonstrated his expertise in field robotics as a key member of the ETH-MAV Team during the 2017 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). His 2018 paper on the team's efforts, with 7 citations, details the development of robust outdoor micro aerial vehicle (MAV) platforms capable of autonomous operation in complex, real-world environments. By bridging theoretical estimation techniques with practical, high-stakes applications, Schindler has made tangible contributions to the advancement of agile, self-balancing robots and autonomous aerial systems, inspiring future work in mobile robotics and sensor integration.