Uthman
Olawoye
Robotics & Navigation Engineer
West Virginia University — Aerospace Engineering
I research cooperative localization of multi-agent robotic systems — building algorithms that let UAVs and UGVs navigate precisely in GNSS-denied environments. From underground tunnels to lunar surfaces.
Roboticist. Navigator.
Problem-solver.
I'm Uthman Olawoye, a PhD candidate in Aerospace Engineering at West Virginia University, where I work in the WVU Navigation Lab under the supervision of Prof. Jason Gross. My research focuses on cooperative localization of multi-agent robotic systems in GNSS-denied environments.
My work spans algorithm design, simulation studies, and real-world experiments — from underground tunnel navigation with UAV/UGV teams to collaborative search-and-rescue missions with the U.S. Air Force and NASA robotic challenges.
Before my PhD, I gained hands-on industry experience at Qualcomm's Location Technology Team, taught control systems at The Polytechnic Ibadan, and built automation systems in manufacturing. I bring both rigorous research and real engineering to every problem.
Research Areas
The core technical domains that drive my work.
Cooperative Multi-Robot Navigation
Designing algorithms for UAV/UGV teams to localize and navigate collaboratively in environments where GPS is unavailable or unreliable.
Factor Graph Optimization
Applying FGO and GTSAM for precise position and velocity estimation, fusing GNSS, IMU, ranging, and LiDAR data in real time.
LiDAR-Based Perception
Using 3D point cloud processing and deep learning (PointPillars) for UAV detection, localization, and object recognition in complex scenes.
SLAM & State Estimation
Simultaneous Localization and Mapping for ground robots in subterranean environments — underground tunnels, GPS-denied urban canyons.
Research highlights
See the Research page for all projects in full.
Collaborative Search & Rescue UAVs — USAF & Kinnami
Integrated AmiShare P2P comms, programmed autonomous cooperative flights via Ardupilot/MAVROS, and validated localization for UAV & pedestrian position estimation.
UAV/UGV Teams in Underground Tunnels
Designed Factor Graph Optimization for drone localization and SLAM for UGV navigation in GNSS-denied subterranean environments with real tunnel experiments.
UAV Position Estimation via LiDAR & PointPillars
Created a 7,000+ scan annotated LiDAR dataset, implemented PointPillars for real-time UAV detection, achieving 30% improvement over traditional clustering methods.
FGO Framework — Qualcomm Location Technology
Developed groundwork for testing Factor Graph Optimization for precise position/velocity estimation, integrating GNSS and motion sensor data at Qualcomm, Santa Clara.
Curriculum Vitae
A snapshot — download the full PDF below.