SBIR-STTR Award

Adaptive Sensor Fusion for Realistic and Autonomous Seabed Models
Award last edited on: 9/7/2022

Sponsored Program
SBIR
Awarding Agency
DOD : DARPA
Total Award Amount
$1,724,703
Award Phase
2
Solicitation Topic Code
HR001120S0019-04
Principal Investigator
Jose Andres

Company Information

Makai Ocean Engineering

Po Box 1206
Kailua, HI 96734
   (808) 259-8871
   makai@makai.com
   www.makai.com
Location: Single
Congr. District: 02
County: Honolulu

Phase I

Contract Number: HR001121C0064
Start Date: 1/5/2021    Completed: 10/4/2021
Phase I year
2021
Phase I Amount
$224,900
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 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, composed of Makai Ocean Engineering (Makai) and Woods Hole Oceanographic Institute (WHOI), 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, multi-domain seafloor model. The proposed effort will leverage Makai’s Digital Terrain Models (DTM) used in the world’s leading submarine cable planning software MakaiPlan, decades of WHOI and Makai experience processing and visualizing seafloor datasets, and team members’ expertise developing embedded, machine learning (ML) algorithms.

Phase II

Contract Number: HR001122C0060
Start Date: 3/29/2022    Completed: 3/28/2024
Phase II year
2022
Phase II Amount
$1,499,803
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.