
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 where a leader navigates via waypoints and followers respond to IR signals, collisions, and freefall events, enabling basic group movement. Leveraging Python’s multithreading and socket programming, Aiden built scripts to manage multiple robots over a network, synchronizing commands and handling per-robot connections. He emphasized code maintainability by providing thorough inline documentation and reorganizing files for clarity. His work established a robust server-side architecture, supporting future robotics experiments and facilitating team onboarding and collaboration.
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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