Martin A. Skoglund

About

Martin A. Skoglund is a researcher whose work bridges precise positioning, autonomous navigation, and acoustic sensing. His primary research areas include real-time kinematic (RTK) GPS performance evaluation, simultaneous localization and mapping (SLAM), and sound source localization using wearable sensor arrays. Skoglund’s most cited work, a 2016 study on low-cost RTK GPS receivers (33 citations), provides a rigorous static and dynamic performance comparison against state-of-the-art systems, using a driving robot on the AstaZero proving ground—a contribution that informs cost-effective autonomous vehicle navigation. In SLAM, he has advanced optimization-based formulations for unmanned aerial vehicles, notably through a nonlinear least-squares approach (13 citations) and a smoothed-estimate method for UAVs using cameras and inertial sensors. His innovative work on a wearable microphone array platform (7 citations) combines inertial sensors and magnetometers to localize stationary sound sources and beamform desired directions, demonstrating a novel fusion of audio and motion sensing. Skoglund’s research consistently emphasizes practical, real-world evaluation, making his contributions valuable for engineers developing autonomous systems and wearable sensing technologies.

Research Focus

Key Achievements

Top Papers

1. 1
   Static and dynamic performance evaluation of low-cost RTK GPS receivers

   33 citations · 2016
2. 2
   A Nonlinear Least-Squares Approach to the SLAM Problem

   13 citations · 2011
3. 3
   Sound Source Localization and Reconstruction Using a Wearable Microphone Array and Inertial Sensors

   7 citations · 2020
4. 4
   Solving The SLAM Problem for Unmanned Aerial Vehicles Using Smoothed Estimates

   3 citations · 2010

Key Collaborators

Contact & Links