AVSLab/basilisk
Nov 2024 – Apr 2026
14 Months active
Languages Used
C++PythonSWIGRSTBashCMakeGitPowerShell
Technical Skills
C++C++ DevelopmentNumerical MethodsObject-Oriented ProgrammingOperator OverloadingPython
juan-g-bonilla
PROFILE
Juan-g-bonilla
Over 14 months, contributed to AVSLab/basilisk by developing advanced simulation frameworks and control systems for robotics and aerospace applications. Delivered features such as stochastic dynamics, orbital mechanics enhancements, and modular MuJoCo integration, focusing on reliability, extensibility, and Python accessibility. Leveraged C++, Python, and CMake to implement robust build automation, cross-platform support, and automated testing pipelines. Introduced JSON-based metadata pipelines for code generation and improved messaging, state management, and payload handling. Emphasized maintainability through targeted refactoring, documentation, and error handling, resulting in scalable, high-fidelity simulations and streamlined developer workflows for both research and production environments.
Overall Statistics
Feature vs Bugs
87%Features
Repository Contributions
146Total
Bugs
6
Commits
146
Features
39
Lines of code
37,501
Activity Months14
Your Network
21 peopleWork History
April 2026
5 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary focusing on key accomplishments for AVSLab/basilisk. Delivered a JSON-based metadata pipeline for C/C++ header parsing and code generation, replacing SWIG XML where applicable to enable typed constructors and field descriptors for payload classes and to tighten integration with the build system.
5 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary focusing on key accomplishments for AVSLab/basilisk. Delivered a JSON-based metadata pipeline for C/C++ header parsing and code generation, replacing SWIG XML where applicable to enable typed constructors and field descriptors for payload classes and to tighten integration with the build system.
April 2026
February 2026
13 Commits • 3 Features
Feb 1, 2026February 2026 monthly overview for AVSLab/basilisk focusing on delivering core orbital mechanics enhancements, stochastic dynamics for atmospheric modeling, and documentation/quality improvements, with strong emphasis on business value and simulation fidelity.
February 2026
13 Commits • 3 Features
Feb 1, 2026February 2026 monthly overview for AVSLab/basilisk focusing on delivering core orbital mechanics enhancements, stochastic dynamics for atmospheric modeling, and documentation/quality improvements, with strong emphasis on business value and simulation fidelity.
January 2026
6 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) focused on delivering realistic, high-value simulation capabilities for attitude control and robust actuator command processing in AVSLab/basilisk. The work enables offline validation of control algorithms, reduces hardware testing risk, and accelerates development cycles by providing ready-to-use MuJoCo-based attitude feedback simulations with reaction wheels and a modular actuator command pipeline with safety safeguards. Documentation and release notes accompany the feature work to improve onboarding and maintainability.
6 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) focused on delivering realistic, high-value simulation capabilities for attitude control and robust actuator command processing in AVSLab/basilisk. The work enables offline validation of control algorithms, reduces hardware testing risk, and accelerates development cycles by providing ready-to-use MuJoCo-based attitude feedback simulations with reaction wheels and a modular actuator command pipeline with safety safeguards. Documentation and release notes accompany the feature work to improve onboarding and maintainability.
January 2026
November 2025
14 Commits • 3 Features
Nov 1, 2025November 2025 monthly summary for AVSLab/basilisk focused on reliability in parallel simulations, deeper Python bindings, and expanded translational motion capabilities. Delivered three integrated feature clusters with strong test coverage, release notes updates, and improved maintainability. Business impact includes more scalable simulations, easier user onboarding with Python, and broader modeling capabilities for translational motion.
November 2025
14 Commits • 3 Features
Nov 1, 2025November 2025 monthly summary for AVSLab/basilisk focused on reliability in parallel simulations, deeper Python bindings, and expanded translational motion capabilities. Delivered three integrated feature clusters with strong test coverage, release notes updates, and improved maintainability. Business impact includes more scalable simulations, easier user onboarding with Python, and broader modeling capabilities for translational motion.
September 2025
2 Commits
Sep 1, 2025September 2025 (AVSLab/basilisk) — Key robustness and data integrity improvements for 2D array recorders. Implemented dynamic extraction of 2D array dimensions to ensure correct payload capture across varying sizes, addressing a stability regression. Major fix: payload recording regression for 2D arrays; release notes updated to document the fix. Result: improved data reliability for downstream analytics and reduced post-release troubleshooting. Commits reflected: 4d2071a7970380b1585b267c7ca538863c5262db (Fix recorders for 2D arrays not working); e01eb8fa4a75f6f0b34af6a51976e7a92df2f5f2 (Update release notes).
2 Commits
Sep 1, 2025September 2025 (AVSLab/basilisk) — Key robustness and data integrity improvements for 2D array recorders. Implemented dynamic extraction of 2D array dimensions to ensure correct payload capture across varying sizes, addressing a stability regression. Major fix: payload recording regression for 2D arrays; release notes updated to document the fix. Result: improved data reliability for downstream analytics and reduced post-release troubleshooting. Commits reflected: 4d2071a7970380b1585b267c7ca538863c5262db (Fix recorders for 2D arrays not working); e01eb8fa4a75f6f0b34af6a51976e7a92df2f5f2 (Update release notes).
September 2025
August 2025
13 Commits • 4 Features
Aug 1, 2025August 2025 (AVSLab/basilisk) continued strengthening control realism, reliability, and developer usability. Focused feature delivery and targeted fixes improved simulation fidelity, tooling, and documentation, enabling faster experimentation and clearer usage guidance for downstream users and researchers.
August 2025
13 Commits • 4 Features
Aug 1, 2025August 2025 (AVSLab/basilisk) continued strengthening control realism, reliability, and developer usability. Focused feature delivery and targeted fixes improved simulation fidelity, tooling, and documentation, enabling faster experimentation and clearer usage guidance for downstream users and researchers.
July 2025
23 Commits • 9 Features
Jul 1, 2025July 2025 impact summary for AVSLab/basilisk: delivered robust messaging and data handling enhancements, expanded UI capabilities, and strengthened deployment/documentation practices. The work enables faster experiment iteration, safer feature rollouts, and clearer developer guidance by improving data capture, message workflows, and payload handling across Recorder integrations, unsubscription flows, and actuator/scenario UIs.
23 Commits • 9 Features
Jul 1, 2025July 2025 impact summary for AVSLab/basilisk: delivered robust messaging and data handling enhancements, expanded UI capabilities, and strengthened deployment/documentation practices. The work enables faster experiment iteration, safer feature rollouts, and clearer developer guidance by improving data capture, message workflows, and payload handling across Recorder integrations, unsubscription flows, and actuator/scenario UIs.
July 2025
June 2025
4 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for AVSLab/basilisk focused on reliability, memory safety, and CI stability. The team delivered improved error handling, safer memory management, and more robust test execution, aligning with business goals of stable simulations and faster issue diagnosis.
June 2025
4 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for AVSLab/basilisk focused on reliability, memory safety, and CI stability. The team delivered improved error handling, safer memory management, and more robust test execution, aligning with business goals of stable simulations and faster issue diagnosis.
May 2025
14 Commits • 1 Features
May 1, 2025Month: 2025-05 — Delivered a comprehensive stochastic dynamics and diffusion framework for AVSLab/basilisk, enabling accurate diffusion models for dynamic objects, along with robust noise handling, pseudo time stepping, and multiple stochastic integrators. The work also included targeted refactors to improve maintainability, improved observability, and early diffusion-task integration within MJScene. Overall, this month advances the product capability in stochastic simulations, improves fidelity, and enhances developer productivity through cleaner abstractions and clearer prints.
14 Commits • 1 Features
May 1, 2025Month: 2025-05 — Delivered a comprehensive stochastic dynamics and diffusion framework for AVSLab/basilisk, enabling accurate diffusion models for dynamic objects, along with robust noise handling, pseudo time stepping, and multiple stochastic integrators. The work also included targeted refactors to improve maintainability, improved observability, and early diffusion-task integration within MJScene. Overall, this month advances the product capability in stochastic simulations, improves fidelity, and enhances developer productivity through cleaner abstractions and clearer prints.
May 2025
April 2025
18 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for AVSLab/basilisk: Delivered modular MuJoCo dynamics integration and StatefulSysModel framework with Python bindings, delivering measurable business value through faster builds, easier customization, and broader Python accessibility. Focused on stability, correctness, and maintainability while enabling data-science workflows with Python.
April 2025
18 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for AVSLab/basilisk: Delivered modular MuJoCo dynamics integration and StatefulSysModel framework with Python bindings, delivering measurable business value through faster builds, easier customization, and broader Python accessibility. Focused on stability, correctness, and maintainability while enabling data-science workflows with Python.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for AVSLab/basilisk: Implemented CI Build Automation with Conan on Linux to automatically install missing system packages in CI and updated Conan profile to permit package manager installation with sudo. This streamlines the build process by ensuring dependencies are met, improving CI reliability and reducing time-to-feedback. No major bugs fixed this month; the focus was on stabilizing Linux CI workflow and reproducibility. Applicable commits: f2dd56518e884e3e3577c0d7fb9b575556656d63.
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for AVSLab/basilisk: Implemented CI Build Automation with Conan on Linux to automatically install missing system packages in CI and updated Conan profile to permit package manager installation with sudo. This streamlines the build process by ensuring dependencies are met, improving CI reliability and reducing time-to-feedback. No major bugs fixed this month; the focus was on stabilizing Linux CI workflow and reproducibility. Applicable commits: f2dd56518e884e3e3577c0d7fb9b575556656d63.
March 2025
February 2025
16 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for AVSLab/basilisk: Focused on stabilizing cross‑platform builds and expanding MuJoCo simulation capabilities while improving code hygiene and documentation. Delivered a Windows DLL copy fix to resolve build-time errors, integrated MuJoCo as a Conan package with runtime support, replay utilities, unit tests, and multi‑platform scenarios, and enhanced CI and documentation. Also improved repository hygiene by excluding user-specific CMake presets from version control, reducing risky commits and keeping the repo clean. These efforts yield more reliable builds, richer simulation tooling, and a cleaner codebase for faster feature delivery and customer value.
February 2025
16 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for AVSLab/basilisk: Focused on stabilizing cross‑platform builds and expanding MuJoCo simulation capabilities while improving code hygiene and documentation. Delivered a Windows DLL copy fix to resolve build-time errors, integrated MuJoCo as a Conan package with runtime support, replay utilities, unit tests, and multi‑platform scenarios, and enhanced CI and documentation. Also improved repository hygiene by excluding user-specific CMake presets from version control, reducing risky commits and keeping the repo clean. These efforts yield more reliable builds, richer simulation tooling, and a cleaner codebase for faster feature delivery and customer value.
December 2024
7 Commits • 5 Features
Dec 1, 2024December 2024 monthly summary for AVSLab/basilisk focusing on reliability, maintainability, and readiness for upcoming MuJoCo integration.
7 Commits • 5 Features
Dec 1, 2024December 2024 monthly summary for AVSLab/basilisk focusing on reliability, maintainability, and readiness for upcoming MuJoCo integration.
December 2024
November 2024
10 Commits • 3 Features
Nov 1, 2024November 2024 — Delivered core architecture improvements in AVSLab/basilisk that broaden state representation flexibility, improve numerical propagation, and lower barriers to experimentation through Python bindings. Key outcomes include polymorphic StateData support integrated with Runge-Kutta propagation, performance-aware state handling, and Python bindings via SWIG for DynParamManager and StateData. These changes improve modeling flexibility, maintainability, and time-to-delivery for feature work.
November 2024
10 Commits • 3 Features
Nov 1, 2024November 2024 — Delivered core architecture improvements in AVSLab/basilisk that broaden state representation flexibility, improve numerical propagation, and lower barriers to experimentation through Python bindings. Key outcomes include polymorphic StateData support integrated with Runge-Kutta propagation, performance-aware state handling, and Python bindings via SWIG for DynParamManager and StateData. These changes improve modeling flexibility, maintainability, and time-to-delivery for feature work.
Activity
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Quality Metrics
Correctness93.4%
Maintainability90.2%
Architecture90.6%
Performance85.2%
AI Usage20.6%
Skills & Technologies
Programming Languages
BashCC++CMakeGitMarkdownPowerShellPythonRSTSWIG
Technical Skills
API DesignAPI UsageAPI designAlgorithmsBuild AutomationBuild SystemBuild System ConfigurationBuild System ManagementBuild SystemsBuild system integrationC++C++ BindingsC++ DevelopmentC++ IntegrationC++ Template Programming
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