AgentSkillsCN

Edge Deployment Skill

针对机器人边缘设备（如 Jetson、嵌入式设备）开展机器学习模型优化与部署

SKILL.md
--- frontmatter
name: Edge Deployment Skill
description: ML model optimization and deployment on robot edge devices (Jetson, embedded)
slug: edge-deployment
category: Deployment
allowed-tools:
  - Bash
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Edge Deployment Skill

Overview

Expert skill for optimizing and deploying machine learning models on robot edge devices including NVIDIA Jetson and embedded systems.

Capabilities

  • •Configure TensorRT optimization for NVIDIA Jetson
  • •Set up ONNX model conversion and optimization
  • •Implement INT8 and FP16 quantization
  • •Configure DeepStream for video analytics
  • •Set up CUDA graph optimization
  • •Implement model pruning and distillation
  • •Configure DLA (Deep Learning Accelerator) deployment
  • •Set up multi-stream inference
  • •Implement ROS2 inference nodes
  • •Profile and benchmark on target hardware

Target Processes

  • •nn-model-optimization.js
  • •object-detection-pipeline.js
  • •rl-robot-control.js
  • •field-testing-validation.js

Dependencies

  • •TensorRT
  • •ONNX Runtime
  • •NVIDIA Jetson SDK
  • •DeepStream

Usage Context

This skill is invoked when processes require deploying ML models on edge devices with optimized inference performance.

Output Artifacts

  • •TensorRT engine files
  • •ONNX optimized models
  • •Quantization configurations
  • •DeepStream pipeline configs
  • •Inference benchmark reports
  • •ROS2 inference node implementations