GenParkEmbodiedSpatial3DOccupancyGridSolver
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GenParkEmbodiedSpatial3DOccupancyGridSolverbuild a 3D occupancy voxel map from my lidar scan and check collision"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
genpark-embodied-spatial-3d-occupancy-grid-solver-skill
Production-grade Physical AI & Robotics skill engineered strictly with Python standard library. Provides real-time spatial intelligence, trajectory generation, and tactile control for autonomous robotic systems via the Model Context Protocol (MCP).
Architecture & Data Flow
flowchart TD
Sensor[3D Depth Sensors / Joint Encoders / Tactile Array] --> Ingest[Telemetry Normalizer]
Ingest --> Core["GenParkEmbodiedSpatial3DOccupancyGridSolver"]
Core --> Kinematics[Robotics Dynamics & Spatial Engine]
Kinematics --> Safety[Boundary & Collision Guardrails]
Safety --> MCPOutput[Standard MCP Tool Result / Control Vector]Related MCP server: genpark-spatial-obstacle-pointcloud-voxel-slicer-skill
Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Standalone MCP Server Launch
Run the native STDIO MCP server:
python mcp_server.pyLicense
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be deployed
Maintenance
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