TensorRT Optimization for Robotics: Accuracy, Latency, and Throughput

This guide provides a practical approach to optimizing models for robotics using TensorRT, focusing on accuracy, latency, and throughput. It emphasizes measuring the complete inference pipeline, including preprocessing and postprocessing, and making failure states visible to operators. Key recommendations include validating ONNX outputs, benchmarking different precision levels on target hardware, and versioning engines for reliable deployment.

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