addinedu-roscamp-7th/roscamp-repo-1
Oct 2025 – Nov 2025
2 Months active
Languages Used
C++CMakeMarkdownPython
Technical Skills
Arm ControlC++C++ DevelopmentCMakeCMakeListsComputer Vision
park619412-oss
PROFILE
Park619412-oss
Over a two-month period, contributed to the addinedu-roscamp-7th/roscamp-repo-1 repository by developing the Packee Arm Controller Core with ROS 2 integration, enabling dual-arm visual servoing and robust automation workflows. Leveraging C++, Python, and ROS2, designed and documented an IBVS-based control architecture, implemented hardware adapters, and enhanced mock testing for multi-arm scenarios. Migrated packaging and control workflows from C++ to Python, introduced vision-driven pickup algorithms, and refined arm motion parameters for improved accuracy. Addressed reliability through targeted bug fixes in arm control nodes, resulting in a scalable, testable foundation that streamlines onboarding and accelerates delivery of automated robotic handling features.
Overall Statistics
Feature vs Bugs
86%Features
Repository Contributions
26Total
Bugs
1
Commits
26
Features
6
Lines of code
11,087
Activity Months2
Your Network
10 peopleWork History
November 2025
11 Commits • 3 Features
Nov 1, 2025Month: 2025-11 | Project: addinedu-roscamp-7th/roscamp-repo-1. Focused on delivering end-to-end automation improvements for PackeeArm, including a migration of packaging to Python, and expanding ROS2-based control with vision integration. Key outcomes include Python-based PackeeArm control workflows and packaging upgrade, ROS2 service-based dual-arm control with vision-driven pickup, and motion/pose refinements for improved accuracy and throughput. Addressed reliability through targeted bug fixes in left/right arm nodes. Result: reduced build complexity, faster automation cycles, and a more robust automated handling pipeline, driving faster time-to-value for packaging and product handling.
11 Commits • 3 Features
Nov 1, 2025Month: 2025-11 | Project: addinedu-roscamp-7th/roscamp-repo-1. Focused on delivering end-to-end automation improvements for PackeeArm, including a migration of packaging to Python, and expanding ROS2-based control with vision integration. Key outcomes include Python-based PackeeArm control workflows and packaging upgrade, ROS2 service-based dual-arm control with vision-driven pickup, and motion/pose refinements for improved accuracy and throughput. Addressed reliability through targeted bug fixes in left/right arm nodes. Result: reduced build complexity, faster automation cycles, and a more robust automated handling pipeline, driving faster time-to-value for packaging and product handling.
November 2025
October 2025
15 Commits • 3 Features
Oct 1, 2025October 2025 performance highlights: Delivered the Packee Arm Controller Core with ROS 2 integration and dual-arm visual servoing, including JetCobot/myCobot adapters and a foundational communication bridge. Completed Planning, Design, and Documentation for the Packee Arm, detailing IBVS-based control, interfaces, service definitions, execution flows, and testing strategies. Enhanced mock testing for multi-arm configurations to improve realism and regression coverage. Improved build and tooling hygiene via cleanup of build metadata and updated README/tests, accelerating onboarding and future iterations. Business impact: provides a scalable, testable foundation for multi-arm automation, reduces integration risk, and enables faster delivery of robust arm control features.
October 2025
15 Commits • 3 Features
Oct 1, 2025October 2025 performance highlights: Delivered the Packee Arm Controller Core with ROS 2 integration and dual-arm visual servoing, including JetCobot/myCobot adapters and a foundational communication bridge. Completed Planning, Design, and Documentation for the Packee Arm, detailing IBVS-based control, interfaces, service definitions, execution flows, and testing strategies. Enhanced mock testing for multi-arm configurations to improve realism and regression coverage. Improved build and tooling hygiene via cleanup of build metadata and updated README/tests, accelerating onboarding and future iterations. Business impact: provides a scalable, testable foundation for multi-arm automation, reduces integration risk, and enables faster delivery of robust arm control features.
Activity
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Quality Metrics
Correctness88.0%
Maintainability86.4%
Architecture87.0%
Performance82.2%
AI Usage24.6%
Skills & Technologies
Programming Languages
C++CMakeMarkdownPython
Technical Skills
Arm ControlC++C++ DevelopmentCMakeCMakeListsComputer VisionControl SystemsDeep LearningDocumentationEmbedded SystemsMockingParameter TuningPythonPython DevelopmentPython development
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