
Anas Himmi integrated a Kalman Filter into the EPFLRocketTeam/2024_C_AV_RPI flight computer navigation pipeline, focusing on enhancing sensor fusion and state estimation for embedded systems. Using C++ and CMake, Anas updated both build processes and data structures to support Kalman-based navigation, enabling more robust processing of sensor data. The work involved resolving merge conflicts and stabilizing the integration to ensure safe incorporation into the main codebase. Although the contribution spanned one feature over a month, the depth of engineering addressed core navigation challenges, laying groundwork for improved reliability in flight computer systems through advanced filtering and software refactoring techniques.
Monthly summary for 2025-03 focused on EPFLRocketTeam/2024_C_AV_RPI. Key work centered on integrating a Kalman Filter into the Flight Computer Navigation pipeline to improve sensor fusion and state estimation, with updates to build and data structures to support Kalman-based navigation.
Monthly summary for 2025-03 focused on EPFLRocketTeam/2024_C_AV_RPI. Key work centered on integrating a Kalman Filter into the Flight Computer Navigation pipeline to improve sensor fusion and state estimation, with updates to build and data structures to support Kalman-based navigation.

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