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In this Intel Chip Chat audio podcast with Allyson Klein: With no GPS in space, how can a rover know its exact location on a lunar surface?
Phil Ludivig, rover navigation engineer with iSpace, Inc. joins Shashi Jain, innovation manager at Intel, to talk about research that applied AI to one of the biggest challenges in space exploration.
Ludivig and Jain, along with other researchers, came together at NASA Frontier Development Lab (NASA FDL) to tackle questions facing NASA and the commercial space industry. Their team took on one of the most fundamental – and answered it a highly inventive way.
Starting with a game engine, the team created a simulated lunar environment to train an AI algorithm that produced the ground truth needed for machine learning. Next, they created synthetic images, called reprojections, from cameras mounted on a rover. AI matched reprojected images to actual orbital images, figuring out terrain features that made sense.
The team used Intel AI DevCloud for inference, an Intel Core i7+ PC and Intel Xeon Scalable processor-based server for synthetic training data generation, and Google Cloud Platform for training.
The same technique can be applied anywhere, on Mars or even areas of Earth where GPS is out of reach.
For details about this and other NASA FDL projects, visit:
Information about Phil Ludivig’s organization is online at:
More about AI at Intel is available at:
- Applying AI to Advance Space Exploration – Intel Chip Chat – Episode 627
- Accelerating AI Inference with Microsoft Azure Machine Learning – Intel Chip…
- Google Cloud: Intel Xeon Scalable Platform at Hyperscale – Intel Chip Chat…
- Supporting the AI Community with Tools and Research from Intel AI Lab – Intel…
- Intel Nervana AI Academy Broadens Access to AI Training – Intel Chip Chat…
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