PX4/PX4-Autopilot
Jun 2026 – Jun 2026
1 Month active
Languages Used
C++
Technical Skills
C++ developmentC++ programmingalgorithm developmentembedded systemsmathematical modelingperformance testing
Elisa Ferrara
PROFILE
Elisa Ferrara
Worked on PX4/PX4-Autopilot to enhance simulation fidelity and estimator accuracy by implementing latitude-dependent gravity using the Somigliana model. Developed a centralized gravity computation helper in C++ with caching to minimize CPU overhead, integrating it into both EKF2 state prediction and simulation components. Refactored simulation code to eliminate duplication and ensure consistent gravity calculations across modules. Added a microbenchmark to quantify performance, achieving a low per-call cost, and introduced unit and regression tests to validate gravity behavior across various latitude scenarios. Demonstrated expertise in C++ development, algorithm design, and embedded systems, focusing on robust, performance-conscious engineering solutions.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
1
Lines of code
241
Activity Months1
Your Network
209 peopleShared Repositories
181
Work History
June 2026
4 Commits • 1 Features
Jun 1, 2026June 2026 performance-focused update for PX4-Autopilot: implemented latitude-dependent gravity using the Somigliana model to improve EKF2 accuracy and simulation fidelity. Centralized gravity computation via LatLonAlt::Wgs84::gravity(), with caching to avoid per-step cost, and reused this gravity helper in both the main filter prediction and the output predictor. Refactored simulation (SIH) to consume the shared gravity helper, removing duplication. Added a microbenchmark to bound the CPU cost of gravity() and included unit/regression tests for gravity across before GPS, near-equator, and high-latitude scenarios. All changes preserve default CONSTANTS_ONE_G behavior until GPS availability. Commit trail shows feature work across gravity helper addition, EKF2 integration, simulation refactor, and gravity benchmark.
4 Commits • 1 Features
Jun 1, 2026June 2026 performance-focused update for PX4-Autopilot: implemented latitude-dependent gravity using the Somigliana model to improve EKF2 accuracy and simulation fidelity. Centralized gravity computation via LatLonAlt::Wgs84::gravity(), with caching to avoid per-step cost, and reused this gravity helper in both the main filter prediction and the output predictor. Refactored simulation (SIH) to consume the shared gravity helper, removing duplication. Added a microbenchmark to bound the CPU cost of gravity() and included unit/regression tests for gravity across before GPS, near-equator, and high-latitude scenarios. All changes preserve default CONSTANTS_ONE_G behavior until GPS availability. Commit trail shows feature work across gravity helper addition, EKF2 integration, simulation refactor, and gravity benchmark.
June 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability95.0%
Architecture100.0%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++
Technical Skills
C++ developmentC++ programmingalgorithm developmentembedded systemsmathematical modelingperformance testingrefactoringsensor fusionsimulationunit testing
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