David Hanley

Centre for Inflammation Research, University of Illinois Urbana-Champaign, University of Illinois System

Papers

Total Citations

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About

David Hanley is a leading researcher in indoor positioning systems and continuum robotics, with a focus on leveraging magnetic anomalies for precise localization. His most impactful work, the MagPIE dataset (2017, 43 citations), provides a publicly available benchmark for evaluating indoor positioning algorithms using magnetic fields, featuring IMU and magnetometer data with centimeter-level ground truth accuracy. Hanley’s research has critically advanced the understanding of how magnetic fields vary with height—a factor often overlooked in planar assumptions. In his 2021 study (20 citations), he demonstrated that building components like steel studs and HVAC systems create height-dependent magnetic signatures, significantly impacting positioning accuracy for robots and handheld devices. This was further validated in his 2018 experimental evaluation (4 citations), where twenty magnetometers mounted on a ground robot revealed substantial field variations from knee to head height. Beyond positioning, Hanley has contributed to medical robotics with his 2023 work on data-driven steering of concentric tube robots (20 citations), enabling precise control in minimally invasive surgeries despite tissue contact. His earlier 2015 work on passive payload mechanisms for quadrotors (8 citations) showcases his versatility in aerial robotics. With over 95 total citations, Hanley’s research bridges fundamental magnetic field physics with practical robotic applications, offering essential tools and insights for researchers in indoor navigation and surgical robotics.