
Contributed to MissouriMRDT/Autonomy_Software by developing and refining navigation and control features for autonomous rover systems. Replaced the existing bicycle model with a unicycle model to improve predictive control, updating related controllers, tests, and documentation to align with the new approach. Introduced a Docker deployment script with NVIDIA runtime support, streamlining containerized experimentation and deployment. Enhanced the maintainability and readability of the Predictive Stanley Controller through code clarity and formatting improvements, reducing future maintenance overhead. Leveraged C++, CMake, and scripting skills throughout, with a focus on algorithm design, DevOps practices, and robust documentation to support ongoing robotics research and development.
November 2025 monthly summary for MissouriMRDT/Autonomy_Software: Focused on improving maintainability and readability of the Predictive Stanley Controller by applying code clarity and formatting enhancements. This work reduces future maintenance costs, improves review velocity, and sets a stronger foundation for upcoming features.
November 2025 monthly summary for MissouriMRDT/Autonomy_Software: Focused on improving maintainability and readability of the Predictive Stanley Controller by applying code clarity and formatting enhancements. This work reduces future maintenance costs, improves review velocity, and sets a stronger foundation for upcoming features.
October 2025 monthly summary for MissouriMRDT/Autonomy_Software focused on navigation model improvements and deployment tooling. Replaced the bicycle model with a Unicycle model to enhance predictive control for rover navigation, accompanied by related controller improvements, angular velocity limit test updates, a Unicycle paper reference, and code cleanups removing bicycle references and updating UnicycleModel author info. Added a Docker deployment script to simplify running autonomy software inside a container with NVIDIA runtime support and proper resource mounting. These changes improve navigation accuracy, streamline experimentation, and reduce deployment friction across containerized environments.
October 2025 monthly summary for MissouriMRDT/Autonomy_Software focused on navigation model improvements and deployment tooling. Replaced the bicycle model with a Unicycle model to enhance predictive control for rover navigation, accompanied by related controller improvements, angular velocity limit test updates, a Unicycle paper reference, and code cleanups removing bicycle references and updating UnicycleModel author info. Added a Docker deployment script to simplify running autonomy software inside a container with NVIDIA runtime support and proper resource mounting. These changes improve navigation accuracy, streamline experimentation, and reduce deployment friction across containerized environments.

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