A high-performance Python wrapper for the Pangolin library designed for real-time 3D visualization of robotics and spatial data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pangolin-utils
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install pangolin-utils using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Pywayne Visualization Pangolin Utils?
Pywayne Visualization Pangolin Utils is a sophisticated 3D visualization toolkit that provides a streamlined Python interface to the Pangolin rendering engine. It is specifically built for developers using Openclaw Skills who need to visualize complex spatial information such as SLAM outputs, IMU data, and robot state estimations in real-time.
By simplifying the interaction with low-level graphics calls, this utility allows for the seamless rendering of points, camera poses, trajectories, and geometric shapes. It serves as a bridge between raw data processing and visual debugging, making it an essential component for any Openclaw Skills project involving 3D computer vision or robotics.
Pywayne Visualization Pangolin Utils Use Cases
- Visualizing real-time SLAM trajectories and dense point cloud reconstructions.
- Monitoring autonomous vehicle or robot states with synchronized camera pose displays.
- Debugging spatial algorithms using the integrated step-by-step frame mode.
- Verifying camera calibration through custom-rendered chessboards and coordinate planes.
- Displaying side-by-side sensor images alongside 3D environmental data.
How Pywayne Visualization Pangolin Utils Works
- Initialize the PangolinViewer instance with defined window dimensions.
- Call the init() method to configure the 3D viewport and initial camera projection.
- Implement a visualization loop that monitors the window status via should_not_quit().
- Update the scene dynamically by adding or clearing points, lines, and trajectories.
- Execute the show() method with an optional delay to render the frame at a specific frequency.
- Close the viewer or join the process thread once the visualization task is complete.
Pywayne Visualization Pangolin Utils Setup
To integrate this utility into your Openclaw Skills development environment, ensure you have the core dependencies installed. The Pangolin library is managed automatically.
# Install the pywayne package containing the utility
pip install pywayne
Basic initialization script:
from pywayne.visualization.pangolin_utils import PangolinViewer
viewer = PangolinViewer(800, 600)
viewer.init()
Pywayne Visualization Pangolin Utils Data Schema & Taxonomy
| Data Type | Format Requirement | Description |
|---|---|---|
| Point Clouds | float32 (N, 3) | Array of spatial coordinates |
| Colors | float32 (N, 3) | RGB values normalized between 0.0 and 1.0 |
| Trajectories | float32 (N, 4) or (N, 7) | Supports SE3 matrices or position+quaternion vectors |
| Quaternions | wxyz or xyzw | Flexible format for orientation data |
| Images | numpy.ndarray | Standard image arrays for 2D UI overlays |
Pywayne Visualization Pangolin Utils Advanced Features
- Main Camera Following: Configure the 3D viewport to automatically track specific moving camera IDs.
- Debugging Step Mode: Pause execution and advance frames manually to inspect granular data changes within Openclaw Skills workflows.
- Multi-Pose Support: Native handling of various SE3 and quaternion formats for broad compatibility with robotics frameworks.
- Custom Plane Rendering: Add transparent geometric planes with labels for spatial reference and boundary visualization.
- Dual Image Display: Support for rendering two independent 2D image streams (e.g., stereo vision) simultaneously.
SKILL.md
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