Questions regarding the TensorRT library of the Chrono::Sensor module

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Zero

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Jun 11, 2026, 3:49:57 AMJun 11
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Hello, everyone. Gentlemen!

I would like to ask, has the reference to the TensorRT library been removed in the newly updated Chrono::Sensor module? And why was it removed?

Dan Negrut

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Jul 1, 2026, 4:39:56 PM (2 days ago) Jul 1
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Hi,

Yes, TensorRT support was removed from Chrono::Sensor. The CHANGELOG gives the reasoning directly:

“The TensorRT feature was removed. With PyChrono now wrapping the Chrono::Sensor module, this feature was superfluous. Users can now transfer data to Python nodes through Chrono::ROS or directly use PyChrono.”

 

One clarification, because that phrasing can read like a one-to-one replacement, and it isn't quite. TensorRT let you run a neural network inside the sensor's filter graph, on the GPU, during the simulation (in-loop inference). The suggested alternatives, Chrono::ROS and PyChrono, are about getting the sensor data out of Chrono so you can process it yourself. So the practical migration is:

  • Before: the model ran in-simulation, on-GPU, as part of the sensor pipeline.
  • Now: you pull the sensor buffers into Python (PyChrono's Get*Data() / NumPy access, or over Chrono::ROS) and run your model there with your own stack (PyTorch, ONNX Runtime, or TensorRT directly).

For the common use case, grab frames and run a model in your own Python code, this is actually more flexible and is probably what most people want. What you give up is the tightly-coupled, in-the-loop GPU inference that never left the simulator. If your workflow depended on that (say, high-rate closed-loop perception running inside the sim), you'll now be doing that inference out-of-loop in Python rather than inside Chrono::Sensor.

 

However, if you think about it, in reality, this is how it happens – the sensor stream is processed elsewhere (before, you had access to privileged information).

 

Source: CHANGELOG.md, "Chrono::Sensor features and updates" section.

 

Dan

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