Avionics-Propulsion-Landers-GT/MonopropUAV
Nov 2025 – Mar 2026
4 Months active
Languages Used
Rust
Technical Skills
Kalman filteringRust programmingalgorithm developmentsensor fusionalgorithm designdocumentation
Favour Adekola
PROFILE
Favour Adekola
Favour Adekolawole developed core autonomy components for the MonopropUAV repository, focusing on robust state estimation and control for UAVs. Over four months, Favour designed and implemented a reusable Extended Kalman Filter library in Rust, supporting sensor fusion from GPS, LiDAR, and IMU sources. The work included modular traits for plug-and-play sensor integration, comprehensive documentation, and a Chebyshev-based solver for trajectory optimization. Favour also enhanced the attitude estimation and control framework with Model Predictive Control and lossless convexification modules, improved error handling, and introduced tunable EKF parameters, demonstrating depth in algorithm development, numerical analysis, and control systems engineering.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
5
Lines of code
1,247
Activity Months4
Your Network
22 peopleShared Repositories
22
Work History
March 2026
2 Commits • 1 Features
Mar 1, 2026Monthly work summary for 2026-03 focusing on EKF robustness and configurability in MonopropUAV. Delivered two key EKF improvements with targeted commits, enhancing navigation reliability and tunability for UAV propulsion system control.
2 Commits • 1 Features
Mar 1, 2026Monthly work summary for 2026-03 focusing on EKF robustness and configurability in MonopropUAV. Delivered two key EKF improvements with targeted commits, enhancing navigation reliability and tunability for UAV propulsion system control.
March 2026
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 focused on enhancing the Attitude Estimation and Control Framework for MonopropUAV. Implemented new library modules for Lossless Convexification and Model Predictive Control (MPC), performed code refactoring, and resolved critical build issues in the EKF pipeline. These changes improve attitude estimation accuracy, control robustness, and maintainability for autonomous operations.
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 focused on enhancing the Attitude Estimation and Control Framework for MonopropUAV. Implemented new library modules for Lossless Convexification and Model Predictive Control (MPC), performed code refactoring, and resolved critical build issues in the EKF pipeline. These changes improve attitude estimation accuracy, control robustness, and maintainability for autonomous operations.
December 2025
2 Commits • 2 Features
Dec 1, 2025Month 2025-12 Performance Summary for Avionics-Propulsion-Landers-GT/MonopropUAV Key features delivered: - EKF Rust Implementation Documentation: Delivered comprehensive documentation detailing features, project structure, core components, and practical usage examples for altitude, attitude, and 2D position estimation. (Commit: 51173bff3f4a7b6d25b5c23abea74787d0fbd64a) - Chebyshev Lossless Solver Baseplate: Implemented baseplate for parameterized, lossless trajectory optimization using Chebyshev polynomials to support UAV trajectory planning. (Commit: 178114ac115731730c835c3208054469491bbc6e) Major bugs fixed: - No major bugs fixed this month. (If any minor issues were addressed, they were not surfaced as blockers in the current scope.) Overall impact and accomplishments: - Strengthened core autonomy capabilities by delivering foundational documentation for the Rust EKF, facilitating safer altitude, attitude, and 2D position estimation workflows. - Established a reusable baseplate for Chebyshev-based trajectory optimization, enabling parameterized, lossless planning in UAV flight paths and setting the stage for performance-oriented optimizations. - Improved onboarding, knowledge transfer, and maintainability within the MonopropUAV codebase, accelerating future development and reviews. Technologies/skills demonstrated: - Rust-based EKF concepts and documentation, with emphasis on real-time estimation components. - Numerical optimization foundations using Chebyshev polynomials for trajectory planning. - Documentation discipline, project structure clarity, and usage examples to support cross-team collaboration.
2 Commits • 2 Features
Dec 1, 2025Month 2025-12 Performance Summary for Avionics-Propulsion-Landers-GT/MonopropUAV Key features delivered: - EKF Rust Implementation Documentation: Delivered comprehensive documentation detailing features, project structure, core components, and practical usage examples for altitude, attitude, and 2D position estimation. (Commit: 51173bff3f4a7b6d25b5c23abea74787d0fbd64a) - Chebyshev Lossless Solver Baseplate: Implemented baseplate for parameterized, lossless trajectory optimization using Chebyshev polynomials to support UAV trajectory planning. (Commit: 178114ac115731730c835c3208054469491bbc6e) Major bugs fixed: - No major bugs fixed this month. (If any minor issues were addressed, they were not surfaced as blockers in the current scope.) Overall impact and accomplishments: - Strengthened core autonomy capabilities by delivering foundational documentation for the Rust EKF, facilitating safer altitude, attitude, and 2D position estimation workflows. - Established a reusable baseplate for Chebyshev-based trajectory optimization, enabling parameterized, lossless planning in UAV flight paths and setting the stage for performance-oriented optimizations. - Improved onboarding, knowledge transfer, and maintainability within the MonopropUAV codebase, accelerating future development and reviews. Technologies/skills demonstrated: - Rust-based EKF concepts and documentation, with emphasis on real-time estimation components. - Numerical optimization foundations using Chebyshev polynomials for trajectory planning. - Documentation discipline, project structure clarity, and usage examples to support cross-team collaboration.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Delivered a reusable Extended Kalman Filter (EKF) library with sensor models for GPS, LiDAR, and IMU to enable robust UAV state estimation. Introduced EKF struct and EKFModel trait to support plug-and-play sensor data processing and state estimation in the MonopropUAV stack. This work lays the foundation for accurate navigation, sensor fusion, and safer autonomous flight. Key commit reference: Add EKF implementation library and models in rust (b3d3c0d7baab598f2ddfc026d940232433841629).
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Delivered a reusable Extended Kalman Filter (EKF) library with sensor models for GPS, LiDAR, and IMU to enable robust UAV state estimation. Introduced EKF struct and EKFModel trait to support plug-and-play sensor data processing and state estimation in the MonopropUAV stack. This work lays the foundation for accurate navigation, sensor fusion, and safer autonomous flight. Key commit reference: Add EKF implementation library and models in rust (b3d3c0d7baab598f2ddfc026d940232433841629).
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Quality Metrics
Correctness90.0%
Maintainability83.4%
Architecture86.6%
Performance83.4%
AI Usage23.4%
Skills & Technologies
Programming Languages
Rust
Technical Skills
Kalman filteringRust programmingalgorithm designalgorithm developmentcontrol systemsdocumentationerror handlingfilter designfiltering techniquesnumerical analysissensor fusiontrajectory optimization
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