MAKAI OCEAN ENGINEERING INC — Department of Defense SBIR Phase II: HR001120S0019-04

MAKAI OCEAN ENGINEERING INC — SBIR Phase II award from Department of Defense.

Phase II SBIR prototype / development signal

  • Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
  • Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
  • Obligated amount $1,499,803 is consistent with substantial Phase II-scale effort; compare to related awards from the same agency.
  • Topic code HR001120S0019-04 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.

Informational capture context from public federal data — not legal or bid advice.

Amount
$1,499,803
Agency
Department of Defense · Defense Advanced Research Projects Agency
Program / Phase
SBIR · Phase II
Topic
HR001120S0019-04
Solicitation
HR001120S0019.I
NAICS
Place of performance
HI
Period
2022-03-29 → 2025-03-28

Description

As autonomy, duration, and complexity of UUV missions increases, so too does the need for access to higher fidelity simulation and planning tools to ensure mission critical success. Advanced UUV fleets are critical for maintaining future subsea military dominance, and the availability of suitable simulation environments for technology and autonomy development is limited, in part due to the significant manual labor required to process and generate simulation models. An adaptive data processing method that uses a variety of multi-modal seafloor sensor and survey data, autonomously generates continuous and environmentally accurate three-dimensional seafloor models, and intelligently inserts and applies man-made or structured obstacles, will not only provide faster and more efficient seafloor modeling but will allow for accelerated development of the autonomous subsea vehicles critical to our subsea forces and operations. The Makai team propose to address this problem by developing a simulation environment synthesis that uses raw data plus adaptive and machine learning software to generate a realistic and continuous three-dimensional high-fidelity seafloor model. The proposed effort will leverage Makai’s Digital Terrain Models (DTM) used in the world’s leading submarine cable planning software MakaiPlan, the state-of-the-art in hydrographic data processing, and team members’ expertise developing embedded, machine learning (ML) algorithms.