Digital Twin Modeling & Software

DEPT OF DEFENSE

Notice type
Sources Sought
Solicitation #
N00173-26-RFI-DS02
NAICS
541715
PSC
AC12
Set-aside
No Set aside used
Posted
May 29, 2026
Response due
June 15, 2026
Place of performance
Washington, DC

What this opportunity is

The Department of Defense is seeking a vendor to develop a high-fidelity digital twin of the Laboratory for Autonomous Systems Research (LASR) facilities and assets in Washington, DC. This opportunity falls under NAICS 541715 and is not set aside for small businesses, meaning all business types can compete. The notice type is a Sources Sought, indicating that the government is gathering information on potential vendors rather than soliciting bids at this stage, which may require interested parties to track the opportunity for future developments.

Analysis by Mindy, grounded in the SAM.gov notice.

Description

Statement of Work - Functional Specifications Modeling of LASR Digital Twin – LASR Facility Introduction: The Laboratory for Autonomous Systems Research (LASR), Code 1700 of the Naval Research Laboratory (NRL) provides facilities, equipment and other resources that enable research in the fields of robotic and autonomous systems (RAS), communication and navigation, human robot interaction and machine learning. To better support this research, the LASR facility requires a high-fidelity digital twin of its facilities, equipment and platforms. Scope: This document describes the minimum technical specifications, performance standards and delivery requirements for a digital twin of the facilities and assets at LASR to be developed by the vendor and delivered to the Naval Research Laboratory, Washington, DC. Delivery: The Digital Twin and associated software will be delivered and uploaded to computers in the Laboratory for Autonomous Systems Research at the Naval Research Laboratory, Washington DC 20375. Description: The Digital Twin will accurately model and simulate the physical environments and various assets within the LASR facility, providing NRL researchers with an easily accessible tool for simulating robotic and autonomous system (RAS) behaviors in realistic digital environments. The Digital Twin shall enable controlled exploration and extensive test and evaluation of RAS across a wide range of conditions in a cost-effective manner not afforded by the physical environment. 1 System Specifications: 1.01 The Digital Twin shall utilize the latest tools and services within the NVIDIA Omniverse Digital Tools and Environment to implement and operationalize the concept. 1.02 The Digital Twin shall include the following components: 1.02.1 Virtual environments of four distinct high bay spaces (outlined below in 1.03.1) with physical properties and behavior parameterized by real world or proxy sensor values 1.02.2 RAS platform models (outlined in 1.04.1) with physical properties, sensors, actuators, and manipulators included as modular components -- 1 of 7 -- 1.02.3 Tools, plug-ins and microservices to support anticipated functionalities including, but not limited to, model import and synthesis from environment scans, model update scripts, automated test and validation scripts, and user interfaces 1.02.4 Validation of the model performance that ensures behaviors and observations in the virtual environment are acceptable approximations of performance in the real physical environment. 1.03 Environment Models Specification: 1.03.1 Models shall be built of LASR environments including four physical spaces within the LASR facility including: 1.03.1.1 Desert High Bay (DHB), a simulated arid terrain environment used for evaluating autonomous ground vehicles and sensors with overall room dimensions of approximately 44 ft × 30 ft × 28 ft. Within the DHB, there is a 25 ft × 18 ft sand pit filled with approximately 2.5 ft of sand, and floor-to-ceiling simulated rock walls ~18 ft high x 35 ft long. The DHB presents a large open volume which, in addition to the sand pit and rock walls, contains structural elements, experimental infrastructure, and overhead equipment that must be modeled. 1.03.1.2 Littoral High Bay (LHB), with simulated coastal and shallow-water environments for testing maritime and amphibious autonomous systems, which has approximate dimensions of 54 ft × 76 ft × 28 ft. Within the LHB, there is a 45 ft × 25 ft pool approximately 5.5 ft deep with a 16-channel directional wave generator. The LHB presents a large open volume and, in addition to the pool, contains structural elements, experimental infrastructure, and overhead equipment that must be modeled. 1.03.1.3 Prototyping High Bay (PHB), a reconfigurable experimental space with approximate dimensions of 150 ft × 75 ft × 30 ft used for the development and evaluation of autonomous systems including aerial vehicles, ground vehicles, and human-system interaction experiments. The PHB presents a large open volume containing various structural elements, experimental infrastructure, and overhead equipment including, but not limited to, windows and doors, wall and ceiling mounting members, modular wall structures, lighting, speakers, cameras, overhead crane, and tables and chairs, that must be modeled. 1.03.1.4 Tropical High Bay (THB), a greenhouse environment designed to replicate a Southeast Asian rainforest ecosystem with overall room dimensions of approximately 60 ft × 40 ft × 46 ft. The THB contains dense tropical vegetation with multi-level canopy structure, natural terrain including a waterfall, stream and pond, rain and fog generation systems, and temperature and humidity control, that must be modeled. -- 2 of 7 -- 1.03.2 The models will utilize scans of the environments provided in E57 and OBJ file formats to the vendor by NRL. 1.03.3 During model creation, evaluations will be performed to ensure the provided scan data matches the actual environments. Identified issues and inaccuracies will either be corrected, with the vendor either performing manual edits to the scan files or requesting rescans from LASR staff. 1.03.4 The models shall create and label separate components within each environment for distinct elements and features, and shall annotate those components with physical attributes include color and other material properties that are parameterized based on known material property data, vendor observations and NRL user input. 1.03.5 Components within the environments to model shall include, but are not limited to: 1.03.5.1 terrain (flooring, sand, rocks, mud, water) 1.03.5.2 wave generation system 1.03.5.3 trees and other plants 1.03.5.4 various wall, ceiling and window surfaces 1.03.5.5 water tanks 1.03.5.6 overhead cranes 1.03.5.7 tables, chairs and shelving 1.03.5.8 lights 1.03.6 The model component parameters shall be capable of tuning and additional modification by the end user and system administrators. 1.03.7 The models s

Source: SAM.gov, as posted. Verify the current solicitation before responding.

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