According to foreign media reports, on June 17, local time, Parallel Domain, which focuses on generating and simulating synthetic data for autonomous driving systems, announced the launch of a revolutionary product-PD Replica.
The product can generate high-fidelity digital twins based on real-world photos, videos and 3D scans, revolutionizing the way autonomous vehicles are developed and tested.
, Parallel Domain Autonomous Driving Test Platform (Photo source: Parallel Domain),PD Replica leverages artificial intelligence (AI) and advanced 3D reconstruction technology to allow customers to create virtual replicas that are almost identical to real-world environments, from city streets to highways.
This product transforms the way cameras, smartphones and drones capture data into an immersive, semantically rich 3D world, allowing autonomous vehicle developers to test their AI systems in a high-fidelity simulation environment, and this kind of high-fidelity simulation environment is basically consistent with real-world conditions and has unprecedented high precision.
The impact of PD Replica has been profound, and autonomous driving developers, many of whom have already partnered with Parallel Domain, can now test their systems in a high-fidelity simulation environment, avoiding the risks and logistical challenges of physical testing.
The technology opens up new possibilities for the development and deployment of autonomous vehicles, and is expected to serve other industries such as manufacturing, healthcare, supply chain, logistics and agriculture in the future.
Recent advances in AI and 3D reconstruction technology power high-fidelity digital twin technology.
PD Replica’s AI technology intelligently processes camera data such as smartphone photos and videos to create pixel-perfect, fully marked, and real-world matching 3D replicas.
This ability to create high-fidelity models benefits from recent advances in AI and 3D technology.
Once the digital twin is created, PD Replica can simulate various sensor patterns, such as lidar point clouds, thermal camera images, and drone views, allowing the autonomous driving system to be fully tested.
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