purdue-arc/sphero-swarm
Jan 2025 – Mar 2026
9 Months active
Languages Used
PythonPygameGit ConfigurationGit IgnoreMarkdowntext
Technical Skills
Game DevelopmentPygameSimulationSimulation DevelopmentAPI IntegrationAlgorithm Design
Alan Kang
PROFILE
Alan Kang
Alan Kang developed and maintained the purdue-arc/sphero-swarm repository, delivering a robust Python-based simulation and control framework for Sphero robot swarms. He engineered grid-based movement, group bonding, and real-time coordinate streaming using technologies such as Pygame, ZeroMQ, and threading. Alan’s work included implementing swarm coordination algorithms, collision avoidance, and a modular driver architecture, enabling scalable multi-robot experiments and remote control. He improved maintainability through code refactoring, documentation, and project restructuring, while enhancing simulation fidelity and testability. His contributions addressed both technical depth and practical deployment, resulting in a reliable platform for robotics research and rapid prototyping of swarm behaviors.
Overall Statistics
Feature vs Bugs
95%Features
Repository Contributions
69Total
Bugs
1
Commits
69
Features
20
Lines of code
5,315
Activity Months9
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Work History
March 2026
4 Commits • 3 Features
Mar 1, 2026March 2026 performance summary for purdue-arc/sphero-swarm: - Focused on delivering safer Sphero movement in a swarm context, improving simulation fidelity, and strengthening code maintainability to enable future scaling. - The month emphasized business value: safer robotic motion, reliable swarm coordination, and easier long-term maintenance to support larger experiments and potential deployments. Key outcomes: - Implemented Sphero straight-line movement mode with a safety toggle and updated simulation to support the new movement style, addressing potential out-of-bounds errors. - Added swarm management and simulation capabilities to coordinate and translate multiple Spheros with improved group handling for scalable experiments. - Performed codebase cleanup and readability improvements, removing deprecated code, standardizing naming (snake_case), clarifying comments, and improving return types to reduce future maintenance overhead.
4 Commits • 3 Features
Mar 1, 2026March 2026 performance summary for purdue-arc/sphero-swarm: - Focused on delivering safer Sphero movement in a swarm context, improving simulation fidelity, and strengthening code maintainability to enable future scaling. - The month emphasized business value: safer robotic motion, reliable swarm coordination, and easier long-term maintenance to support larger experiments and potential deployments. Key outcomes: - Implemented Sphero straight-line movement mode with a safety toggle and updated simulation to support the new movement style, addressing potential out-of-bounds errors. - Added swarm management and simulation capabilities to coordinate and translate multiple Spheros with improved group handling for scalable experiments. - Performed codebase cleanup and readability improvements, removing deprecated code, standardizing naming (snake_case), clarifying comments, and improving return types to reduce future maintenance overhead.
March 2026
February 2026
8 Commits • 1 Features
Feb 1, 2026February 2026 (purdue-arc/sphero-swarm) delivered end-to-end bonded groups movement for Sphero swarms, enabling coordinated formations and rotation. Implemented the BondedGroup lifecycle (constructor, center calculation, group movement, bonding logic, validation) and integrated it with the Algorithm and driver components. Merged rotation support into the feature set and stabilized the core framework, with work spanning simulation and translation paths. Added checkpoint saving to improve recoverability of experiments and refactored driver.py to consume the new BondedGroup API, improving maintainability and testability. This work increases reliability for multi-robot experiments, enabling more complex formations and faster iteration, using Python-based tooling and clean architectural boundaries.
February 2026
8 Commits • 1 Features
Feb 1, 2026February 2026 (purdue-arc/sphero-swarm) delivered end-to-end bonded groups movement for Sphero swarms, enabling coordinated formations and rotation. Implemented the BondedGroup lifecycle (constructor, center calculation, group movement, bonding logic, validation) and integrated it with the Algorithm and driver components. Merged rotation support into the feature set and stabilized the core framework, with work spanning simulation and translation paths. Added checkpoint saving to improve recoverability of experiments and refactored driver.py to consume the new BondedGroup API, improving maintainability and testability. This work increases reliability for multi-robot experiments, enabling more complex formations and faster iteration, using Python-based tooling and clean architectural boundaries.
November 2025
10 Commits • 4 Features
Nov 1, 2025November 2025: Delivered core swarm control enhancements and production readiness for purdue-arc/sphero-swarm. Key features delivered include refined Sphero swarm control with diagonal movement tuning and initialization constants; and a slower Spotter for debugging with configurable frame dimensions. Production-mode readiness was achieved by switching to run_server in place of test_controls, and environment stability was reinforced via dependency updates. These changes improved swarm accuracy, reliability, and deployment readiness, enabling faster iteration and robust performance in live scenarios.
10 Commits • 4 Features
Nov 1, 2025November 2025: Delivered core swarm control enhancements and production readiness for purdue-arc/sphero-swarm. Key features delivered include refined Sphero swarm control with diagonal movement tuning and initialization constants; and a slower Spotter for debugging with configurable frame dimensions. Production-mode readiness was achieved by switching to run_server in place of test_controls, and environment stability was reinforced via dependency updates. These changes improved swarm accuracy, reliability, and deployment readiness, enabling faster iteration and robust performance in live scenarios.
November 2025
October 2025
9 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for purdue-arc/sphero-swarm: Delivered foundational Sphero Spotter features enabling real-time coordinate streaming and remote control via a ZeroMQ-based client-server channel. Introduced SpheroCoordinate model, threaded listener with lifecycle management, graceful shutdown, and enhanced protocol documentation, laying the groundwork for scalable swarm coordination. Completed project restructuring to improve maintainability by removing outdated YOLO experiments, updating model loading paths, and cleaning the perception module. Fixed critical threading issues to stabilize streaming and control paths, and updated dependencies to reflect the new architecture. These changes collectively enable robust real-time swarm sensing/control, reduce technical debt, and accelerate onboarding and future feature work.
October 2025
9 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for purdue-arc/sphero-swarm: Delivered foundational Sphero Spotter features enabling real-time coordinate streaming and remote control via a ZeroMQ-based client-server channel. Introduced SpheroCoordinate model, threaded listener with lifecycle management, graceful shutdown, and enhanced protocol documentation, laying the groundwork for scalable swarm coordination. Completed project restructuring to improve maintainability by removing outdated YOLO experiments, updating model loading paths, and cleaning the perception module. Fixed critical threading issues to stabilize streaming and control paths, and updated dependencies to reflect the new architecture. These changes collectively enable robust real-time swarm sensing/control, reduce technical debt, and accelerate onboarding and future feature work.
September 2025
5 Commits • 2 Features
Sep 1, 2025September 2025 monthly summary for purdue-arc/sphero-swarm focused on onboarding, maintainability, and foundational scaffolding for new capabilities. Delivered concrete documentation, repository hygiene improvements, and an initial program scaffold to accelerate future feature work. These changes reduce onboarding time, minimize accidental large-file commits, and establish a solid base for upcoming development.
5 Commits • 2 Features
Sep 1, 2025September 2025 monthly summary for purdue-arc/sphero-swarm focused on onboarding, maintainability, and foundational scaffolding for new capabilities. Delivered concrete documentation, repository hygiene improvements, and an initial program scaffold to accelerate future feature work. These changes reduce onboarding time, minimize accidental large-file commits, and establish a solid base for upcoming development.
September 2025
April 2025
8 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for purdue-arc/sphero-swarm focusing on Sphero swarm simulation UI/rendering, movement realism, and testing infrastructure. Key work delivered stabilized and expanded the simulation environment, improved motion fidelity, and strengthened test coverage while maintaining a clear focus on business value and developer efficiency.
April 2025
8 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for purdue-arc/sphero-swarm focusing on Sphero swarm simulation UI/rendering, movement realism, and testing infrastructure. Key work delivered stabilized and expanded the simulation environment, improved motion fidelity, and strengthened test coverage while maintaining a clear focus on business value and developer efficiency.
March 2025
8 Commits • 3 Features
Mar 1, 2025March 2025 monthly summary for purdue-arc/sphero-swarm: Delivered core coordination features and stability improvements for a swarm of Sphero objects, enabling cohesive formations and safer movement in simulations. Significant progress on grid-based positioning, proximity-based bonding, movement control, and a cleaned, well-documented simulation environment. These efforts reduce risk in multi-robot demos and accelerate ongoing development.
8 Commits • 3 Features
Mar 1, 2025March 2025 monthly summary for purdue-arc/sphero-swarm: Delivered core coordination features and stability improvements for a swarm of Sphero objects, enabling cohesive formations and safer movement in simulations. Significant progress on grid-based positioning, proximity-based bonding, movement control, and a cleaned, well-documented simulation environment. These efforts reduce risk in multi-robot demos and accelerate ongoing development.
March 2025
February 2025
15 Commits • 1 Features
Feb 1, 2025February 2025 performance snapshot for Purdue-ARC sphero-swarm: - Delivered a complete Sphero-based swarm simulation framework and driver enabling scalable multi-sphero experiments. Core movement logic executed on a triangular grid with rendering hooks, and collision/distance handling using EPSILON, plus color cycling across spheros for clear visualization. - Implemented a driver/interface to initialize and control multiple spheros, and established a field-based validation system with initial server communication groundwork to support remote orchestration and data collection. - Achieved early multi-sphero scalability (documented improvements to handle more than 6 spheros) and ongoing refactoring to improve readability and future extensibility. - Refined class design and state management for spheroids (direction tracking) and consolidated the 3-sphero workflow. Business and technical impact: accelerates rapid prototyping of swarm behaviors, enables reproducible experiments, and lays the foundation for telemetry, remote control, and integration with higher-level planning.
February 2025
15 Commits • 1 Features
Feb 1, 2025February 2025 performance snapshot for Purdue-ARC sphero-swarm: - Delivered a complete Sphero-based swarm simulation framework and driver enabling scalable multi-sphero experiments. Core movement logic executed on a triangular grid with rendering hooks, and collision/distance handling using EPSILON, plus color cycling across spheros for clear visualization. - Implemented a driver/interface to initialize and control multiple spheros, and established a field-based validation system with initial server communication groundwork to support remote orchestration and data collection. - Achieved early multi-sphero scalability (documented improvements to handle more than 6 spheros) and ongoing refactoring to improve readability and future extensibility. - Refined class design and state management for spheroids (direction tracking) and consolidated the 3-sphero workflow. Business and technical impact: accelerates rapid prototyping of swarm behaviors, enables reproducible experiments, and lays the foundation for telemetry, remote control, and integration with higher-level planning.
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments, business impact, and technical achievements for purdue-arc/sphero-swarm. Delivered an initial Sphero robot simulation with a triangular grid using Pygame, establishing a reusable sandbox for robotics experimentation and algorithm validation. Implemented the rendering loop, grid visualization, and input handling to support rapid iteration on path planning and behavior development. Subsequent updates improved project clarity and usability by increasing TRIANGLE_SIZE and renaming the grid script for a variant of the simulation.
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments, business impact, and technical achievements for purdue-arc/sphero-swarm. Delivered an initial Sphero robot simulation with a triangular grid using Pygame, establishing a reusable sandbox for robotics experimentation and algorithm validation. Implemented the rendering loop, grid visualization, and input handling to support rapid iteration on path planning and behavior development. Subsequent updates improved project clarity and usability by increasing TRIANGLE_SIZE and renaming the grid script for a variant of the simulation.
January 2025
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Quality Metrics
Correctness80.2%
Maintainability81.4%
Architecture75.4%
Performance71.6%
AI Usage22.4%
Skills & Technologies
Programming Languages
Git ConfigurationGit IgnoreMarkdownPygamePythontext
Technical Skills
API IntegrationAlgorithm DesignAlgorithm DevelopmentAlgorithm ImplementationCode CleanupCode OrganizationCode RefactoringComputer VisionConcurrencyConstants ManagementControl SystemsDebuggingDocumentationDriver DevelopmentEmbedded Systems
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