
Aiden developed foundational multi-robot coordination features for the purdue-arc/sphero-swarm repository, focusing on scalable control systems for Sphero robots. He implemented a Python-based leader-follower framework, enabling waypoint navigation and synchronized responses to events like collisions and freefall. Leveraging socket programming, multithreading, and serialization, Aiden built scripts to manage multiple robots over a network, ensuring reliable command execution and error handling. He emphasized maintainability by providing thorough code documentation and reorganizing project files for clarity. The work addressed the need for repeatable, synchronized robotics experiments and improved team onboarding, demonstrating depth in server-side development and embedded systems integration.

March 2025 performance summary for purdue-arc/sphero-swarm. This period focused on delivering coordinated multi-robot control capabilities and improving code maintainability to accelerate future experiments and team onboarding. Key outcomes include feature delivery, better code readability, and readiness for scaling the robotics experiments across additional robots.
March 2025 performance summary for purdue-arc/sphero-swarm. This period focused on delivering coordinated multi-robot control capabilities and improving code maintainability to accelerate future experiments and team onboarding. Key outcomes include feature delivery, better code readability, and readiness for scaling the robotics experiments across additional robots.
February 2025 monthly summary for purdue-arc/sphero-swarm: Delivered foundational leader-follower coordination and a scalable multi-robot control framework in Python, with server scaffolding and thorough documentation to accelerate future work.
February 2025 monthly summary for purdue-arc/sphero-swarm: Delivered foundational leader-follower coordination and a scalable multi-robot control framework in Python, with server scaffolding and thorough documentation to accelerate future work.
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