NVIDIA WEBINAR
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Date: Thursday, November 5, 2020
Time: 9:00am – 10:00am PT
Duration: 1 hour
Time: 9:00am – 10:00am PT
Duration: 1 hour
The NVIDIA Isaac SDK is a developer toolbox for accelerating the development and deployment of AI-powered robots. At its core, it features the Isaac Engine—a framework that allows robotics developers to deploy applications on edge devices like the NVIDIA Jetson AGX Xavier™—and computers powered by NVIDIA discrete GPUs. It also includes high-performance algorithms for robot perception and planning, as well as a growing set of sensors. The Isaac SDK is ideal for accelerating development for manufacturers, researchers, and startups by making it easier to add AI into next-generation robots for perception, navigation, and manipulation.
Join this webinar to learn how to:
- Train a 3D pose estimation network (an Isaac GEM) using Isaac SIM.
- Deploy 3D pose estimation network on Jetson AGX Xavier.
- Build robotics apps in Isaac and ROS using ROS camera drivers Nodes and Isaac perception GEMS (all in a simulated factory of the future).
- Understand an end-to-end description of application graph flow with Isaac GEMs in ISAAC Sim.
WEBINAR REGISTRATION
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Speakers
Nyla Worker
Data Scientist, NVIDIANyla is a data scientist in the solution architecture organization at NVIDIA focused on simulation and deep learning within embedded devices. Within NVIDIA, she has worked on deep learning edge applications for robotics, as well as for autonomous vehicles. Nyla’s previous projects include accelerating and profiling inference applications at eBay and research on distributed machine learning techniques at the University of Minnesota.
Swapnesh Wani
Data Scientist, NVIDIASwapnesh Wani is a data scientist in the Solutions Architecture and Engineering group at NVIDIA working on developing applications with the NVIDIA Isaac robotics platform. Prior to NVIDIA, Swapnesh earned his Master's degree in Mechatronics and Robotics from New York University, where he studied and worked on path planning, swarm robotics, and deep learning applications for robotics.
Zoe Ryan
Solution Architect, NVIDIAZoe is a Solution Architect at NVIDIA. She started with work in embedded systems and simulation and is now working in GPU-accelerated SciPy SIgnal code. Prior to joining NVIDIA, Zoe earned her BS in Computer Science and Mathematics from Harvey Mudd College and worked as an R&D intern at AMP Robotics, where she did research into depth camera technology.
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