
Elias Cordero developed and maintained the RoboCupJunior-Soccer-Open-League-2025 robotics stack, delivering a robust perception-to-control pipeline for autonomous soccer robots. He engineered real-time ball and goal detection using OpenMV and OpenCV, integrating Python and C++ for embedded systems and microcontroller programming. His work included UART-based data serialization, state-machine-driven control, and repository refactoring to improve maintainability. By implementing camera calibration, coordinate transformation, and sensor integration, Elias enabled reliable navigation and autonomous decision-making. The repository reflects disciplined version control and modular design, resulting in a reusable, competition-ready robotics platform that balances technical depth with practical maintainability for ongoing development.

February 2026 monthly summary for the RoboCupJunior-Soccer-Open-League-2025 project. Delivered the Soccer Robot Control System feature, focusing on movement, ball detection, and goal targeting. This work establishes the core autonomy required for competitive play and forms a reusable module set for future iterations. No major bugs reported this month; groundwork laid for reliability and testability.
February 2026 monthly summary for the RoboCupJunior-Soccer-Open-League-2025 project. Delivered the Soccer Robot Control System feature, focusing on movement, ball detection, and goal targeting. This work establishes the core autonomy required for competitive play and forms a reusable module set for future iterations. No major bugs reported this month; groundwork laid for reliability and testability.
November 2025: Delivered a foundational Robotic Soccer Control System enabling a player to detect and interact with the ball and goals through sensor and motor integration. Established hardware-software integration and set the stage for autonomous play, contributing to competition readiness for RoboCupJunior-Soccer-Open-League-2025.
November 2025: Delivered a foundational Robotic Soccer Control System enabling a player to detect and interact with the ball and goals through sensor and motor integration. Established hardware-software integration and set the stage for autonomous play, contributing to competition readiness for RoboCupJunior-Soccer-Open-League-2025.
October 2025 focused on strengthening perception, expanding coordinate communication, and improving maintainability for the RoboCup Open-League stack. Key features delivered include hardened ball-following logic, cleanup and refactor of the OpenMV codebase, and the implementation of dual-arc and ball coordinate transmission/reading. Major bug fixes addressed day-label accuracy and camera orientation for Sunday/Monday entries, reducing data-labeling errors. Hardware and firmware stability were improved via Memoria Flash integration and a robust firmware reinstall flow, complemented by arc assignment and motor-control enhancements with Arduino-based control. Overall, these efforts boosted autonomous reliability, faster iteration, and clearer module boundaries, delivering tangible business value and technical capability for competition readiness.
October 2025 focused on strengthening perception, expanding coordinate communication, and improving maintainability for the RoboCup Open-League stack. Key features delivered include hardened ball-following logic, cleanup and refactor of the OpenMV codebase, and the implementation of dual-arc and ball coordinate transmission/reading. Major bug fixes addressed day-label accuracy and camera orientation for Sunday/Monday entries, reducing data-labeling errors. Hardware and firmware stability were improved via Memoria Flash integration and a robust firmware reinstall flow, complemented by arc assignment and motor-control enhancements with Arduino-based control. Overall, these efforts boosted autonomous reliability, faster iteration, and clearer module boundaries, delivering tangible business value and technical capability for competition readiness.
September 2025: Delivered end-to-end enhancements across perception, navigation, and control to boost autonomous performance and reliability for RoboCup Junior Open League 2025. Key features delivered: autonomous ball chasing with a state-machine and non-blocking tracking; vision-based object detection with LED feedback and UART data transmission; camera calibration and coordinate transformation improvements for accurate real-world localization; UART reliability fix ensuring complete 8-byte packet reception; and Arquero Arduino-based line-following robot with gyroscope-driven orientation. Business value: more robust autonomous behavior under dynamic play, reliable data communication, and a solid hardware-software foundation for future iterations. Technologies demonstrated: real-time control, computer vision, calibration/homography, UART protocol engineering, Arduino/gyroscope integration.
September 2025: Delivered end-to-end enhancements across perception, navigation, and control to boost autonomous performance and reliability for RoboCup Junior Open League 2025. Key features delivered: autonomous ball chasing with a state-machine and non-blocking tracking; vision-based object detection with LED feedback and UART data transmission; camera calibration and coordinate transformation improvements for accurate real-world localization; UART reliability fix ensuring complete 8-byte packet reception; and Arquero Arduino-based line-following robot with gyroscope-driven orientation. Business value: more robust autonomous behavior under dynamic play, reliable data communication, and a solid hardware-software foundation for future iterations. Technologies demonstrated: real-time control, computer vision, calibration/homography, UART protocol engineering, Arduino/gyroscope integration.
August 2025 focused on strengthening the perception-to-action loop for the RoboCupJunior-Soccer Open League project. Delivered two integrated features in IITA-Proyectos/RoboCupJunior-Soccer-Open-League-2025: (1) OpenMV-based orange ball detection with 3D pose estimation and UART transmission to the Teensy, including data scaling, reliability improvements, and power/activity LEDs; (2) Teensy integration and repository refactor to support UART data reception/interpretation in C++, with a state machine to decode position and direction and cleanup/removal of outdated camera code. The work improves data fidelity, real-time responsiveness, and project maintainability, setting a solid foundation for competition-grade perception and control.
August 2025 focused on strengthening the perception-to-action loop for the RoboCupJunior-Soccer Open League project. Delivered two integrated features in IITA-Proyectos/RoboCupJunior-Soccer-Open-League-2025: (1) OpenMV-based orange ball detection with 3D pose estimation and UART transmission to the Teensy, including data scaling, reliability improvements, and power/activity LEDs; (2) Teensy integration and repository refactor to support UART data reception/interpretation in C++, with a state machine to decode position and direction and cleanup/removal of outdated camera code. The work improves data fidelity, real-time responsiveness, and project maintainability, setting a solid foundation for competition-grade perception and control.
During July 2025, delivered an end-to-end ball-tracking and UART data pipeline between OpenMV and the robot controller, enabling autonomous ball handling for RoboCup Junior Open League. Implemented and hardened the data packet format, including scaling/packing and reliability fixes, and added a Teensy-side UART receiver with OpenMV data decoding for coordinates, angle and direction, plus an extra 'sentido' value. Established directory-based organization for UART data printing and iterated on the module naming (gemini) to improve maintainability. The work reduces sensor-to-actuator latency and data corruption risk, providing a robust foundation for autonomous control and future features. Key accomplishments were achieved through a focused feature set and disciplined version control, reflected in iterative commits across the data-pipeline components.
During July 2025, delivered an end-to-end ball-tracking and UART data pipeline between OpenMV and the robot controller, enabling autonomous ball handling for RoboCup Junior Open League. Implemented and hardened the data packet format, including scaling/packing and reliability fixes, and added a Teensy-side UART receiver with OpenMV data decoding for coordinates, angle and direction, plus an extra 'sentido' value. Established directory-based organization for UART data printing and iterated on the module naming (gemini) to improve maintainability. The work reduces sensor-to-actuator latency and data corruption risk, providing a robust foundation for autonomous control and future features. Key accomplishments were achieved through a focused feature set and disciplined version control, reflected in iterative commits across the data-pipeline components.
June 2025 monthly summary for IITA-Proyectos/RoboCupJunior-Soccer-Open-League-2025: focused on delivering a robust perception feature for autonomous navigation and performing essential repository maintenance to reduce technical debt and improve collaboration. The work emphasizes business value through stable, reusable code and reliable sensor processing for RoboCup tasks.
June 2025 monthly summary for IITA-Proyectos/RoboCupJunior-Soccer-Open-League-2025: focused on delivering a robust perception feature for autonomous navigation and performing essential repository maintenance to reduce technical debt and improve collaboration. The work emphasizes business value through stable, reusable code and reliable sensor processing for RoboCup tasks.
In May 2025, delivered targeted enhancements to the RoboCup Junior Open League project: orange ball detection, angle calculation, and direction mapping improvements, with telemetry exposure for debugging. The X-coordinate is now mapped to a 0-100 range, and angle/direction reporting was refined to support control needs and easier troubleshooting. These changes stabilized perception, improved control reliability, and reduced tuning time, directly contributing to higher match readiness and maintainability. The work consolidated updates to the detection pipeline and control reporting in IITA-Proyectos/RoboCupJunior-Soccer-Open-League-2025, with four commits focused on the relevant script (nombre bonito.py) to implement the changes.
In May 2025, delivered targeted enhancements to the RoboCup Junior Open League project: orange ball detection, angle calculation, and direction mapping improvements, with telemetry exposure for debugging. The X-coordinate is now mapped to a 0-100 range, and angle/direction reporting was refined to support control needs and easier troubleshooting. These changes stabilized perception, improved control reliability, and reduced tuning time, directly contributing to higher match readiness and maintainability. The work consolidated updates to the detection pipeline and control reporting in IITA-Proyectos/RoboCupJunior-Soccer-Open-League-2025, with four commits focused on the relevant script (nombre bonito.py) to implement the changes.
Concise monthly summary for 2025-04 focusing on business value and technical achievements. Key feature delivered: OpenMV ball tracking and object detection script for RoboCupJunior-Soccer-Open-League-2025. The script initializes the OpenMV camera, configures color parameters to detect a specific colored ball, continuously captures frames to locate the ball center, and computes basic angle estimates using the provided camera parameters. This work establishes an automated perception capability for ball localization, improving reliability of autonomous behaviors and accelerating iteration cycles for competition readiness. Commit reference c37b732958217950a468329179db119d182499a1 is included for traceability.
Concise monthly summary for 2025-04 focusing on business value and technical achievements. Key feature delivered: OpenMV ball tracking and object detection script for RoboCupJunior-Soccer-Open-League-2025. The script initializes the OpenMV camera, configures color parameters to detect a specific colored ball, continuously captures frames to locate the ball center, and computes basic angle estimates using the provided camera parameters. This work establishes an automated perception capability for ball localization, improving reliability of autonomous behaviors and accelerating iteration cycles for competition readiness. Commit reference c37b732958217950a468329179db119d182499a1 is included for traceability.
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