A specialized technical reference for processing 3D point cloud data and configuring LiDAR scanning systems.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lidar
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 lidar 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 LiDAR Reference?
The LiDAR skill for Openclaw Skills serves as a comprehensive technical knowledge base and command suite for developers and engineers working with Light Detection and Ranging technology. It provides instant access to point cloud processing workflows, scan pattern types, and coordinate system integration protocols.
By utilizing this skill, users can streamline the complex tasks of filtering, classifying, and visualizing 3D spatial data. It bridges the gap between hardware scanner configuration and software-side data processing, ensuring high-fidelity mapping and surveying outcomes across various industrial applications.
LiDAR Reference Use Cases
- Processing and converting industrial point cloud data formats like LAS, LAZ, and PCD.
- Configuring hardware scanners for high-precision autonomous vehicle or surveying tasks.
- Managing georeferencing and IMU/GNSS integration for mobile mapping units.
- Planning LiDAR survey missions using standardized quality assurance checklists.
- Evaluating software tools like CloudCompare or PDAL for specific 3D meshing projects.
How LiDAR Reference Works
- The user invokes the skill via the Openclaw Skills interface to access specific LiDAR domain knowledge.
- Commands are executed through a modular script system to retrieve reference data on formats, scanners, or processing pipelines.
- The skill references local data directories or specified environment variables to guide data management.
- Output provides actionable technical specifications or workflow steps for tools like LAStools or PCL.
- Developers use the provided checklists to validate survey planning before physical scanner deployment.
LiDAR Reference Setup
To install and configure this skill within your Openclaw Skills environment, use the following steps:
# Clone the repository containing the skill
git clone https://github.com/bytesagain/ai-skills.git
# Navigate to the lidar directory
cd ai-skills/lidar
# (Optional) Set the custom data directory in your environment
export LIDAR_DIR="~/.lidar/"
# Verify the installation
scripts/script.sh help
LiDAR Reference Data Schema & Taxonomy
The LiDAR skill organizes information based on the following technical taxonomy:
| Data Type | Description | Supported Formats |
|---|---|---|
| Point Cloud | Raw and compressed spatial data | LAS, LAZ, PCD, E57, PLY, XYZ |
| Georeferencing | Coordinate system metadata | WGS84, UTM, Local |
| Hardware Specs | Scanner manufacturer data | Velodyne, SICK, Leica, FARO, Ouster |
| Processing Tools | Software integration guides | CloudCompare, PDAL, PCL, LAStools |
All configurations are tracked via the LIDAR_DIR environment variable, which defaults to the user's home directory.
LiDAR Reference Advanced Features
- Multi-format support for seamless transition between geospatial (LAS) and robotic (PCD/PLY) data environments.
- Automated survey planning checklists to ensure data integrity in industrial applications.
- Detailed IMU/GNSS integration logic for mobile and airborne LiDAR systems.
- Comprehensive software tool matrix for selecting the right processing library (PCL vs. PDAL) for specific 3D tasks.
- Modular command structure allowing for integration into larger Openclaw Skills automation workflows.
SKILL.md
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