Data Augmentation Pipeline for Zero-Shot Sim-to-Real Transfer in Vision-Based Robot Navigation
We developed a data augmentation pipeline to enhance the training of vision-based navigation models for robotics, addressing the challenges of limited real-world data.
Safe Autonomous Taxiing with Vision-Based Navigation
TaxiNet is a vision-based deep learning model developed to enable autonomous vehicles to follow a designated line safely during aircraft taxiing, a crucial application for assured…
Global, Seasonal Mars Frost Maps
Global frost Martian maps derived from five remote sensing datasets and processed with tools like CNNs and other data science techniques. Publicly available on JMARS
GenAI Agent for Interacting with Robots (https://github.com/nasa-jpl/rosa)
ROSA is an AI agent that integrates with the ROS ecosystem to help develop and operate robots using natural language. It is able to read live telemetry data from robotics systems…
Artificial Intelligence Leveraged Information Capture and Exploration (ALICE) (ITMX)
The project will streamline the archiving of information and build an explorable knowledge graph of organizational communications. This project seeks to provide several significan…
TxP: Artificial Intelligence for Curation (AI-Cure)
The AI-CURE project will integrate advanced AI and machine learning models to automate and standardize data curation across NASA’s SMD databases.
TxP: Federated Data Discovery and Content Creation (FDDCC) KDP-Formulation (ITMX)
The FDDCC project is guided by a set of core objectives aimed at transforming how data is accessed, managed, and utilized across the agency. These objectives focus on enhancing da…
Fast Machine Learning Lidar Surrogate Simulator: For Pristine Clear Sky
ML base lidar radiative transfer simulation for clear sky
A Neural Network Parametrization of Volumetric Cloud Fraction Profiles Using Satellite Observations and MERRA-2 Reanalysis Meteorological Data
Cloud Parameterization to improve climate model
Intelligent Chatbot for Science using Microsoft Copilot
It uses Microsoft's Large Language model with scientifically curated information from NASA's VEDA (Visualization, Exploration, and Data Analysis) platform to assist users in searc…
Cache-Augmented Generation Document Search (converted to collective)
Cache-Augmented Generation Document Search
Module for Event Driven Operations on Spacecraft (MEDOS)
MEDOS, a flight-tested onboard decision engine
Remote Coordination, Actuation, and Planning (ReCAP) Cooperative MultiAgent Architecture
ReCAP provides an architecture for lightweight, efficient coordination of highly-capable agents in a comms-limited environment. By providing agents with high-level, lightweight in…
Foundation Model for Lunar Science
The purpose of Lunar FM is to overcome the limitations of traditional, task-specific Machine Learning (ML) models in analyzing the vast, diverse, and long-term datasets collected…
JSC NC PRA Cut Set Tool
Probabilistic Risk Assessment (PRA) identifies minimal cut sets - smallest combination of simultaneous failures to cause a system or mission failure.
JSC SMA NT Paper WAD Data Extraction
This application aims to provide the Quality Flight Equipment Division with a strong paper Work Authorization Document (WAD) data extraction capability using AI models. The data i…
AI Based Digital Twin Interoporability Schema
Using IEEE 2874 Spatial Web standard to implement a new Hyperspace Modeling Language (HSML) and Hyperspace Transaction Protocol (HSTP) to establish communications among heterogene…
Deep Learning for Flood Mapping (DELTA)
DELTA simplifies machine learning for satellite imagery.
cFS High Performance Computing Framework (cFS HPCF)
The core Flight System (cFS) High Performance Computing Framework (HPCF) provides an environment to support a wide variety of Science work, to inlcude AI and ML.
OCO2/3 Bad Pixel Map
A machine learning approach is developed to improve the bad pixel map that masks damaged or unusable pixels in the imaging spectrometers of the Orbiting Carbon Observatory-2 and -…
SpecTF Clouding Screening for Imaging Spectroscopy
A deep learning model for accurate, data-driven cloud detection in imaging spectroscopy data.
Decision Theoretic Planning
Algorithms to plan and optimize different outcomes
Cloud avoidance for Atmospheric Retrieval Missions
Methods for atmospheric retrieval of earth science data.
Dynamic, Intelligent, Tomographic Imaging
Methods for analyzing 3D imaging data