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About

Kevin Meier is a robotics researcher whose work sits at the intersection of autonomous aerial navigation and simultaneous localization and mapping (SLAM). He is best known for his contributions to motion planning for agile unmanned aerial vehicles, particularly his development of motion primitives that enable fast, obstacle-avoiding flight through complex, cluttered environments such as dense forests. His foundational research in this area, first presented in 2013 and expanded into a highly influential 2015 publication that has garnered 85 citations, introduced two families of 3D circular motion primitives complete with the control inputs necessary to execute them, offering a practical and elegant framework for real-world aerial autonomy. Beyond motion planning, Meier has made notable strides in structured mapping, pioneering a SLAM approach that replaces traditional sparse feature points with Bézier curves as landmark primitives. This "Visual-Inertial Curve SLAM" work, developed across a 2016 conference paper and a 2017 journal publication with 21 citations, enables full six-degrees-of-freedom pose estimation while generating geometrically meaningful maps suitable for downstream robot planning tasks. Taken together, Meier's research reflects a consistent drive to make autonomous robots faster, smarter, and more spatially aware in unstructured real-world environments.