ASTER LABS, INC. — National Aeronautics and Space Administration STTR Phase I: T11

ASTER LABS, INC. — STTR Phase I award from National Aeronautics and Space Administration.

Amount
$149,987
Agency
National Aeronautics and Space Administration
Program / Phase
STTR · Phase I
Topic
T11
Solicitation
STTR_23_P1
NAICS
Place of performance
MN
Period
2023-07-31 → 2024-09-02

Description

This program will develop an innovative Augmented Reality Navigation (ARNAV) application to help guide astronauts through important tasks within and about space habitats that require navigation and guidance capabilities. Using advanced vision and inertial processing combined with novel Rapidly-exploring Random Tree* (RRT*) algorithms for path planning and Random Finite Set (RFS)-based localization, the novel ARNAV software will provide efficient, optimal, and effective route guidance to human operators by leveraging in-network databases and the environmental data around them. Resulting AR information and visual cues will be relayed to a handheld mobile device with portability to heads up displays (HUDs), and provide key, streamlined, and real-time navigational updates throughout important and mission-critical tasks and procedures. The software architecture will balance provision of relevant and meaningful data with rich AR visualizations, while limiting extensive non-essential feedback, in order to ensure effective, yet practical, operation. Pattern and feature recognition algorithms, including pre-processing delineation routines, 3-D coordinate tracking for feature recognition, utilities for mitigating scene clutter and primary error sources, and the innovative path optimization and localization strategies will be integrated into a prototype ARNAV application. The ARNAV framework will include access to all developed algorithms, database and mapping structures, processing architectures, and a user interface design for AR overlays. Phase I will focus on developing the associated algorithms and ARNAV software application for simulations and performance assessment in representative emulated testing, along with human usability evaluations, to establish accuracy and effectiveness measures for the system.