Deploying aerial perception models on onboard UAV compute: inference runtimes, model export and quantization, and hardware-constrained engineering trade-offs.
8 evidence-linked resources in this topic
Moving trained aerial perception models onto onboard UAV compute with export, quantization and runtime choices that fit power and latency budgets.
Topic reviewed 2026-08-16 · Membership is an editorial index, not a compatibility or performance claim.
Stack layers: edge_ai · perception_localization · hardware
This topic groups the release-backed edge inference records that OpenFly can verify from their official repository or documentation. The page is an entry point for comparing an inference runtime, an NPU toolkit or an export helper without treating them as interchangeable. Deployment support, supported hardware and performance figures are recorded only when the official source states them; measured throughput, certification and compatibility claims remain outside the page unless a SourceRef records them. Resource cards expose verification status, maintenance signal, source tier and retrieval date so the reader can move from the topic explanation to the underlying evidence.
Topic membership is an editorial index, not a compatibility or performance claim. Verify each resource through its SourceRef, retrieval date, and verification status.
jetson-inference is NVIDIA's vision inference toolkit for Jetson devices, providing detection/classification/segmentation examples and TensorRT integration for onboard UAV AI.
ONNX Runtime is a cross-platform inference engine that lets UAV developers deploy ONNX models across CPU, GPU and NPU backends with one format.
OpenVINO is Intel's open inference toolkit for optimizing and deploying AI on Intel CPUs, GPUs and VPUs, relevant for vision workloads on x86 edge computers.
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
RKNN-Toolkit2 is Rockchip's official toolchain for converting and deploying models to RK series NPUs such as RK3588, the main path for RK-based companion computers.
TensorRT is NVIDIA's inference SDK for high-performance deep learning on GPUs and Jetson devices, the primary runtime family for UAV edge AI deployments.
Implementation of popular deep learning networks with TensorRT network definition API
An easy to use PyTorch to TensorRT converter