![]() ![]() ![]() We are excited to see even more advances brought to photorealistic data-driven simulation including: policy learning, testing and verification, augmented reality. New applications and benchmarks: VISTA has enabled many new advances on the algorithmic and applications side. VISTA aims to convert offline (open-loop) datasets into closed-loop testbeds, for faithful evaluations. ![]() Conversely, policies can be extensively stress tested and certified in VISTA prior to deployment.Ĭlosed-loop (active) testing: Passive evaluation on pre-collected datasets provides a mediocre evaluation metric for control. Policies can be trained in VISTA for deployment in reality. Sim-to-real and real-to-sim: Ability to transfer to and from reality and the corresponding digital twins built in VISTA. We highly encourage contributions to the community code. All code is written in Python and is highly modular, customizable, and extensible. On the Options screen, choose from the following tabs: General. Research friendly API: VISTA was designed with research in-mind. To get the best performance with your system, you may want to adjust some of the Train Simulator options. God bless and good luck i didnt find anything. You should also be able to find some tutorials on YouTube on how to do that. Different sensing modalities, environments, dynamics, and tasks with varying complexity are supported. I think you need something called RW tools. Highly flexible and photorealistic data-driven simulation: VISTA is a platform for transforming real-world data into virtual worlds for embodied agent simulation. ![]()
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