OpenHUTB/nn
Sep 2025 – Dec 2025
4 Months active
Languages Used
OpenCVPythonC++MarkdownOBJXMLTXTYAML
Technical Skills
Computer VisionDeep LearningObject DetectionObject-Oriented ProgrammingPython ProgrammingRobotics
东海帝王
PROFILE
东海帝王
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
22Total
Bugs
0
Commits
22
Features
12
Lines of code
1,233,573
Activity Months4
Your Network
159 people
Work History
December 2025
8 Commits • 4 Features
Dec 1, 2025December 2025: Built a modular robot simulation, sensor, and mapping testbed in OpenHUTB/nn that enables end-to-end autonomous navigation validation. Key features delivered include: 1) Robot Motion & Gazebo Simulation Framework with differential controller, YAML config, XACRO model, and Gazebo world; 2) Sensor Simulation Suite (Radar, Camera, Depth) integrated with Gazebo/RViz for perception and mapping; 3) Mujoco-WalkerE3 Simulation with MJDATA.TXT and MJMODEL.TXT; 4) SLAM-based Navigation & Mapping with map saving/serving launch files. Major bug fixes included resolving integration conflicts (#3101) to stabilize builds across motion, sensors, and world configurations. Overall impact: accelerates development, reduces integration risk, and provides a reproducible testbed for autonomous navigation; Demonstrated technologies: Gazebo, RViz, XACRO, YAML, ROS, Mujoco, SLAM, mapping, and depth sensing.
8 Commits • 4 Features
Dec 1, 2025December 2025: Built a modular robot simulation, sensor, and mapping testbed in OpenHUTB/nn that enables end-to-end autonomous navigation validation. Key features delivered include: 1) Robot Motion & Gazebo Simulation Framework with differential controller, YAML config, XACRO model, and Gazebo world; 2) Sensor Simulation Suite (Radar, Camera, Depth) integrated with Gazebo/RViz for perception and mapping; 3) Mujoco-WalkerE3 Simulation with MJDATA.TXT and MJMODEL.TXT; 4) SLAM-based Navigation & Mapping with map saving/serving launch files. Major bug fixes included resolving integration conflicts (#3101) to stabilize builds across motion, sensors, and world configurations. Overall impact: accelerates development, reduces integration risk, and provides a reproducible testbed for autonomous navigation; Demonstrated technologies: Gazebo, RViz, XACRO, YAML, ROS, Mujoco, SLAM, mapping, and depth sensing.
December 2025
November 2025
5 Commits • 2 Features
Nov 1, 20252025-11 monthly performance summary focused on delivering end-to-end robot simulation capabilities, stabilizing the development workflow, and improving data/documentation. The work demonstrates strong cross-backend integration, architecture clarity, and hands-on modeling that directly accelerates testing and feature delivery for robotic navigation tasks.
November 2025
5 Commits • 2 Features
Nov 1, 20252025-11 monthly performance summary focused on delivering end-to-end robot simulation capabilities, stabilizing the development workflow, and improving data/documentation. The work demonstrates strong cross-backend integration, architecture clarity, and hands-on modeling that directly accelerates testing and feature delivery for robotic navigation tasks.
October 2025
6 Commits • 5 Features
Oct 1, 2025OpenHUTB/nn — 2025-10 monthly summary: Delivered an integrated brick-handling enhancement suite spanning visualization, perception, control, and automation. Key outcomes include UR5e wrist2_0 3D model integration for realistic visualization and simulation; a Python-based Brick-carrying Simulation Framework with comprehensive tests for movement, pathfinding, obstacle avoidance, and brick pickup/drop; a real-time CV distance measurement system with ROI-based calibration and live feedback; a YOLO-based Brick Detection Module with training/testing scripts and updated usage docs; and a Carry Bricks Service (C++ Client/Server) with an accompanying launch/demo to showcase end-to-end operation. These deliverables improve development velocity, reliability of robotic workflows, and business value by enabling safer, faster validation and deployment of brick-handling capabilities.
6 Commits • 5 Features
Oct 1, 2025OpenHUTB/nn — 2025-10 monthly summary: Delivered an integrated brick-handling enhancement suite spanning visualization, perception, control, and automation. Key outcomes include UR5e wrist2_0 3D model integration for realistic visualization and simulation; a Python-based Brick-carrying Simulation Framework with comprehensive tests for movement, pathfinding, obstacle avoidance, and brick pickup/drop; a real-time CV distance measurement system with ROI-based calibration and live feedback; a YOLO-based Brick Detection Module with training/testing scripts and updated usage docs; and a Carry Bricks Service (C++ Client/Server) with an accompanying launch/demo to showcase end-to-end operation. These deliverables improve development velocity, reliability of robotic workflows, and business value by enabling safer, faster validation and deployment of brick-handling capabilities.
October 2025
September 2025
3 Commits • 1 Features
Sep 1, 2025September 2025: Delivered an integrated Robot Perception, Simulation, and Navigation Enhancement for OpenHUTB/nn. Key advancements include consolidating perception, object detection, and pose estimation with state fusion for humanoid robots, adding a basic running simulation, and enabling obstacle detection/avoidance using simulated sensors and a camera feed. These capabilities improve autonomous navigation reliability, expand testability in a safe simulated environment, and provide a strong foundation for production-ready robotics workloads.
September 2025
3 Commits • 1 Features
Sep 1, 2025September 2025: Delivered an integrated Robot Perception, Simulation, and Navigation Enhancement for OpenHUTB/nn. Key advancements include consolidating perception, object detection, and pose estimation with state fusion for humanoid robots, adding a basic running simulation, and enabling obstacle detection/avoidance using simulated sensors and a camera feed. These capabilities improve autonomous navigation reliability, expand testability in a safe simulated environment, and provide a strong foundation for production-ready robotics workloads.
Activity
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Quality Metrics
Correctness82.2%
Maintainability81.8%
Architecture82.8%
Performance77.8%
AI Usage26.4%
Skills & Technologies
Programming Languages
C++MarkdownOBJOpenCVPythonTXTXMLYAML
Technical Skills
3D ModelingActionlibC++ developmentC++ programmingComputer VisionData ScienceDeep LearningDocumentationGazeboImage ProcessingMachine LearningObject DetectionObject-Oriented ProgrammingOpenCVPathfinding Algorithms
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