ZVISION announced it’s using the NVIDIA Isaac Sim advanced simulator to create powerful tools for industrial sensing solution validation, addressing high-performance LiDAR simulation for increased applications and fully adaptive testing.
The tool targets robotics simulation applications and synthetic data generation and is used to train and test real-world robots for complex applications more efficiently, recreate realistic robot interactions, and validate performance in various scenarios. ZVISION claims it reduces development costs, testing, and data acquisition while speeding time to market.
NVIDIA Isaac Sim employs physics-based rendering to reproduce obstacles of multiple shapes and sizes to form a functional scene. Users can then validate the performance and capabilities of LiDAR against the complexity and uncertainty of that scene.
This digital twin enables robotics developers to determine which performance modes are suitable for an application based on solutions for complex edge cases. Developers and researchers can also use a variety of Isaac Sim’s tools, including simulation of robot dynamics to test control algorithms, simulation of robot sensors to generate realistic cameras, depth and segmentation images, LiDAR perception, IMU, simulation of testing algorithms in different environments and condition scenarios, and providing training sets of random objects and attributes.
ZVISION’s MEMS LiDAR portfolio includes ML-30s+ short-range LiDAR and ML-Xs forward long-range MEMS LiDAR. The ML series LiDAR models defined by Isaac Sim simulation software are expected to be instrumental in advancing industrial sensing solutions development.
