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Into the Omniverse: How OpenUSD-Based Simulation and Synthetic Data Generation Advance Robot Learning
- Universal Scene Description (OpenUSD) provides a scalable and interoperable data framework for developing virtual worlds where robots can learn how to be robots.
- NVIDIA Isaac Sim is advancing perception AI-based robotics simulation.
- Companies can reduce time to deployment and improve robot performance across a variety of use cases.
- Simulation is a crucial tool for the creation of physically accurate environments where robots can learn through trial and error, refine algorithms and even train AI models using synthetic data.
- With a new reference workflow, developers can accelerate the generation of synthetic 3D datasets with generative AI using OpenUSD NIM microservices.
- Humanoid robots are the next wave of embodied AI, but they present a challenge at the intersection of mechatronics, control theory and AI.
- With NVIDIA Isaac Lab, developers can train humanoid robot policies at scale via simulations.
- Partners across industries are using Isaac Sim, Isaac Lab, Omniverse, and OpenUSD to design, simulate and deploy smarter, more capable autonomous machines.
- Wandelbots integrates its NOVA platform with Isaac Sim to create physics-based digital twins and intuitive training environments, simplifying robot interaction and enabling seamless testing, validation, and deployment of robotic systems in real-world scenarios.
- For more on optimizing OpenUSD workflows, explore the new self-paced Learn OpenUSD training curriculum that includes free DLI courses for 3D practitioners and developers.
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