NVIDIAGameWorks
Influence of Scenario Positioning on Simulation Results in IsaacSim
Description In using NVIDIA's, we've observed that the positioning of replicated scenarios within the simulation environment can significantly influence the outcomes of experiments. This issue aims to address the need for consistent and controlled scenario positioning to ensure reliable and reproducible results.
Specific Scenario
I am testing a deformable body which is attached to a cube at half its length. The other half can move freely from a vertical position, and I want to assess the bending of this body. I made up to 500 copies of this scenario within the environment in order to study the effects of various parameters.
However, I recognized that even when using the same parameters for all copies, the behavior is very different, with up to 50 percent more overhang (see figure)
. If I simulate the same setup, I get approximately the same distribution of results, indicating that the results are nearly deterministic and are influenced by the positioning of the scenario in the global environment.
Impact
-
Inconsistent Results: Significant variability in the simulation results makes it challenging to draw reliable conclusions and impacts the overall validity of the experiments.
-
Reproducibility Issues: Difficulty in replicating experiments due to the positional variability of scenarios affects the ability to perform consistent research.
-
Compromised Accuracy: The accuracy of simulations is critically affected, which is essential for the integrity of research outcomes.
Steps Taken Utilized various time steps to assess the impact of temporal resolution. Enhanced determinism to reduce variability. Adjusted maximum position iterations to explore different convergence criteria.
Request for Feedback We invite feedback from the community for additional strategies to address the influence of scenario positioning on simulation results.
This is a legitimate concern that I am not sure how to best address. Even if we could decrease the impact of random factors like world space position distribution on the outcomes, it would simply mean you would uniformly get one of the many random outcomes you plot above, and none of the others, which in my opinion is not necessarily better for all use cases.
