Efficient Learning for Control of Autonomous Mobility in Navigating Obstacles (EL-CAMINO (EL-CAMINO)

Capability Need/Knowledge Gap: ESDMD, SMD, and STMD have all highly ranked the gap in high progress rate autonomous surface mobility. Systems must travel at unprecedented speeds using new sensing and computing, requiring more capable algorithms. Objectives: Train faster and more capable onboard localization algorithms to learn models for combining camera images and lidar scans leveraging recent advances in model-based learning from terrestrial robotics

Deliverables: Software implementation of EL-CAMINO. Software documentation of the method along with test results. Conference or journal paper detailing findings

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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