David Harvie
Papers
1
Total Citations
2
H-Index
1
About
David Harvie’s research lies at the intersection of robotics, autonomous navigation, and sensor fusion, with a particular focus on enabling reliable vehicle movement in GPS-denied environments. His most cited work, a 2019 study on inertial measurement units fused with odometry, provides a critical comparison of four IMU types for dead-reckoning navigation using an Extended Kalman Filter. This research offers practical guidance for designers of robots and autonomous ground vehicles, addressing the challenge of maintaining accurate positioning when satellite signals are unavailable. By systematically evaluating sensor performance, Harvie’s work helps advance the robustness of autonomous systems in real-world, constrained scenarios. While his citation count is still growing, his contributions are directly relevant to engineers developing navigation solutions for indoor, underground, or other GPS-limited settings. Harvie’s research underscores the importance of sensor selection and algorithm design in creating dependable autonomous platforms, making his work a valuable resource for students and researchers entering the field of mobile robotics and state estimation.
Research Focus
Key Achievements
Top Papers
- 1