Skillget

genpark-embodied-trajectory-quintic-spline-smoother-skill

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 7 GitHub stars
Code Gecti
  • Code scan — Scanned 4 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested

Bu listing icin henuz AI raporu yok.

SUMMARY

GenPark Physical AI quintic polynomial trajectory smoother with continuous boundary constraints (position, velocity, acceleration), and analytic jerk minimization.

README.md

genpark-embodied-trajectory-quintic-spline-smoother-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["GenParkEmbodiedTrajectoryQuinticSplineSmoother"]
    Core --> Kinematics[Robotics Dynamics & Spatial Engine]
    Kinematics --> Safety[Boundary & Collision Guardrails]
    Safety --> MCPOutput[Standard MCP Tool Result / Control Vector]

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.

Yorumlar (0)

Sonuc bulunamadi