SBIR/STTR Research Award

RASTR – Ultra-Fast Smart LiDAR Sensor for Terrain Mapping

Award identifier 33715920cc02d120e33b1b27e9bac32133e376ee0ffe6b9a2ac30191cb055666Awarding agency National Aeronautics and Space Administration

Award amount

$149,986

Program and phase

STTR · Phase I

Award year

2024

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
ASTROBOTIC TECHNOLOGY INC
Proposal award date
2024-08-11
Contract end date
2025-09-08
UEI
JAQ3W2MGVNV1
Solicitation number
STTR-2024-Phase 1
Topic code
T9

Research abstract

Planetary landing systems are constrained by performance, size, weight, and power (SWaP), and cost of active hazard detection (HD) sensor systems that enable real-time terrain mapping and safe site selection. The time it takes an HD sensor system to scan, produce an elevation map that corrects for spacecraft motion, and compute safe landing sites is a critical bottleneck that requires trading fuel mass (delta-V) with scan resolution and accuracy in order to achieve a desired level of mission assurance. A low-SWaP sensor capable of accurately scanning a target landing region to a resolution of 10 cm or better in just two seconds would enable lower cost planetary landers while providing hazard detection capabilities that enhance landing safety and mission assurance, including payload deployment onto the surface. Astrobotic’s RApid Scanning Terrain Resolver (RASTR) sensor solution addresses this lander mission assurance bottleneck by increasing the responsiveness and adaptability of the LiDAR sensor. RASTR will reduce the amount of time and power needed generate accurate terrain maps in real time. Astrobotic will combine its heritage high performance space-grade computing, flight-ready LiDAR processing algorithms, and validated physics-based simulation and terrain modeling tools with a state-of-the-art on-chip ultra-long-range frequency modulated continuous wave (FMCW) LiDAR commercial product and novel single-shot depth estimation machine learning algorithms. Building a system to better optimize around an increased scanning speed and lower SWaP and cost is critical to reducing the barriers to entry of integrating this sensor type into NASA’s Commercial Lunar Payload Services (CLPS) landers. Existing space-grade HD sensor system components do not take advantage of economies of scale (e.g., the autonomous vehicle and drone markets), resulting in cost and lead times being a limiting factor to commercial capabilities.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

52 SBIR/STTR records share this UEI (2010–2025). Reported award amounts total $33,759,467. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: National Aeronautics and Space Administration, Department of Defense

Agency intelligence

National Aeronautics and Space Administration

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