Rob Kemp’s Post

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

Announced at #GTC24, NVIDIA Isaac Perceptor, optimized on Jetson Orin, uses multiple cameras for 3D surround perception to detect hazards invisible to standard 2D lidar. Using robust AI-based depth estimation, GPU-accelerated 3D reconstruction, and semantic segmentation, see how a mobile robot can work more safely alongside humans.

VFusedSeg3D uses a cutting-edge approach that fuses point-based LiDAR backbone features with camera semantic features for the first time. This breakthrough architecture is trained entirely on a single RTX 3090 GPU, delivering high performance and efficiency. To learn more about VFusedSeg3D read the paper: https://lnkd.in/d8G_9zHk Explore our work on GitHub: https://lnkd.in/dew4vSPQ Stay updated! Follow us for more insights and updates on our latest research and projects! #vfusedseg3d #ai #technology #vsearch #research.

Exploring the future of construction! Spent a chunk of today diving into how #TeamSkender is leveraging the latest tech and AI to redefine what’s possible in construction. It’s incredible to see the R&D behind selecting tech that truly adds value for our clients and partners (h/t Ben Stocker). I was especially excited to read this NVIDIA blog that showcases two Skender projects! With the power of AI, RTX GPUs, photogrammetry, LiDAR and gaussian splats, builders like Skender are capturing, modeling and visualizing projects with precision like never before. These #contech innovations are just a few of the tools that allow us to gather data faster and smarter, delivering even better insights, efficiency and quality to our clients. Next-level, inspiring stuff! Read NVIDIA's article: https://lnkd.in/gb5q9wuv