• Profiled state estimation pipeline and reduced end-to-end latency by 25%

• Improved lifecycle manager via per-module resource usage monitoring and more robust module bringup

• Traced critical software issues back to hardware design faults, reduced post-flight file transfer time by 20x

• Evaluated and bugfixed state estimation stack for drones using ROS2, C++, and Python

• Migrated nodes from ROS1 to ROS2, added lifecycle and composition support to reduce all-core CPU usage by 75%, single-core peak usage by 50%, and large-message passing latency by a factor of 10

• Developed scalable pipeline to integrate robot data into benchmark; corrected systemic odometry measurement drift by detecting loop closures and performing bundle adjustment using Python, C++, ROS, Docker, and Maplab

• Selected and installed sensors on robot using C++, Python and ROS, wrote tooling for recording and managing data using Bash and Python, and recorded robot dataset

• Developed scalable pipeline to integrate robot data into benchmark; corrected systemic odometry measurement drift by detecting loop closures and performing bundle adjustment using Python, C++, ROS, Docker, and Maplab

• Selected and installed sensors on robot using C++, Python and ROS, wrote tooling for recording and managing data using Bash and Python, and recorded robot dataset