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GenParkEmbodiedSpatial3DOccupancyGridSolver

GenParkEmbodiedSpatial3DOccupancyGridSolver

Official
by Alpha-Park
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Python
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genpark-embodied-spatial-3d-occupancy-grid-solver-skill

Organization Model Context Protocol Zero-Dependency Python Version License

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: nexus3d

Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Standalone MCP Server Launch

Run the native STDIO MCP server:

python mcp_server.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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    Resources

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      Enables autonomous robotic systems to perform real-time 3D occupancy voxel mapping, raycast-based Bayesian occupancy updates, and sphere collision checking through standard MCP tools.
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    • GenParkEmbodiedTrajectoryQuinticSplineSmoother MCP Server

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      Enables autonomous robotic systems to generate and smooth trajectories with continuous position, velocity, and acceleration boundary constraints, analytic jerk minimization, spatial intelligence, and tactile control through MCP tools.
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