II.
LibraryProcess overview
Reference · livelib-process:robotics-simulation--neural-network-edge-optimization
specializations/robotics-simulation/neural-network-edge-optimization overview
Neural Network Model Optimization for Edge Deployment - Optimize neural network models for deployment on robot edge devices including quantization, pruning, TensorRT conversion, and runtime optimization.
Attributes
displayName
specializations/robotics-simulation/neural-network-edge-optimization
description
Neural Network Model Optimization for Edge Deployment - Optimize neural network models for
deployment on robot edge devices including quantization, pruning, TensorRT conversion, and runtime optimization.
libraryPath
library/specializations/robotics-simulation/neural-network-edge-optimization.js
specialization
robotics-simulation
references
- - TensorRT: https://developer.nvidia.com/tensorrt
- - ONNX Runtime: https://onnxruntime.ai/
- - OpenVINO: https://docs.openvino.ai/
example
const result = await orchestrate('specializations/robotics-simulation/neural-network-edge-optimization', {
modelName: 'detection_model',
targetDevice: 'jetson-orin',
optimizationLevel: 'fp16'
});
usesAgents
- ml-robotics-engineer
- simulation-test-engineer
- simulation-optimization-expert
- ros-expert
Outgoing edges
lib_applies_to_domain1
- domain:robotics·DomainRobotics
lib_belongs_to_specialization1
- specialization:robotics-simulation·Specialization
lib_implements_workflow1
- workflow:simulation-validation-cycle·WorkflowSimulation Validation Cycle
lib_involves_role1
- role:research-engineer·RoleResearch Engineer
lib_requires_skill_area2
- skill-area:motion-planning·SkillAreaMotion Planning
- skill-area:sensor-fusion·SkillAreaSensor Fusion
uses_agent1
- lib-agent:robotics-simulation--ros-expert·LibraryAgentros-expert
Incoming edges
None.