SBIR/STTR Research Award

N221-033 - Perception System for Situational Awareness and Contact Detection for Unmanned Underwater Vessels -- 22-003

Award identifier d234072c34f7c38777812945534ec370c2c94a8fe6882c5deb49f65b5e6fe25aAwarding agency Department of Defense · Navy

Award amount

$140,000

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
METRON INCORPORATED
Proposal award date
2022-07-25
Contract end date
2023-01-23
UEI
EN78W198KUG7
Solicitation number
22.1
Topic code
N221-033

Research abstract

The objective of this project is to develop a sense and avoid perception system for unmanned underwater vessels (UUVs) to support safe maneuvering and navigation in both the surface and the undersea domains. The market for UUVs has been growing rapidly, and with it, demand for obstacle avoidance systems. Growth is happening in the defense, commercial, and scientific sectors. It is worth acknowledging upfront that safely bringing an underwater vehicle to the surface is a complex problem. Human beings aboard submarines equipped with large, sophisticated sensors go through years of training to understand how to interpret sonar data in order to develop situational awareness on the surface. Automating this workflow requires a deep understanding of the sensors and the algorithms involved at each stage of the processing chain, how human operators make decisions, and an awareness of regulations and procedures, like COLREGs. For decades, Metron has been developing and transitioning advanced sonar and data fusion algorithms to the submarine fleet. Over the past decade, Metron has built large UUVs outfitted with our custom sensor systems and prototype collision avoidance algorithms. In recent years, we have made significant strides in applying automation at each stage of the sonar processing chain and have been an industry pioneer in obstacle avoidance algorithms for water-borne vehicles.   Given the myriad of UUV designs that exist, the sought-after collision avoidance system must be able to work with different sensor configurations to be generally useful. This proposal outlines a plan to leverage some of Metron's successes to create an extensible multi-sensor data fusion guidance platform called RASCAL (Reconfigurable Autonomous Sensing and Collision Avoidance pLatform). During Phase II, a prototype multi-sensor hardware system will be built for small-class UUVs. RASCAL will encompass a set of algorithms with clearly defined interfaces to this prototype hardware and to the other UMAA components. The long-term vision for RASCAL is to become the surfacing and collision avoidance service within UMAA with specification-defined interfaces to sensing hardware using industry standards whenever possible. RASCAL’s algorithms will be designed from the ground up to work with different sensor configurations. Further, UI tools can be provided to assist UUV designers with insight into the collision avoidance performance implications of varying sensor placements.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

194 SBIR/STTR records share this UEI (1988–2025). Reported award amounts total $79,536,370. Reported amounts are not federal obligations.

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

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Commerce, Department of Health and Human Services

Agency intelligence

Department of Defense

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