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Monitoring and Inspecting Dirty Nukes Including Generating Heatmaps of Terrain (MIDNIGHT)

Award Information
Agency: Department of Homeland Security
Branch: Countering Weapons of Mass Destruction
Contract: 70RWMD20C00000003
Agency Tracking Number: FY19.1-H-SB019.1-010-0018-II
Amount: $999,978.35
Phase: Phase II
Program: SBIR
Solicitation Topic Code: H-SB019.1-010
Solicitation Number: FY19.1
Timeline
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-09-10
Award End Date (Contract End Date): 2022-09-09
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138-4555
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Daniel Stouch
 Senior Robotics Software Engineer
 (617) 491-3474
 dstouch@cra.com
Business Contact
 Mark Felix
Title: Director of Contracts
Phone: (617) 491-3474
Email: contracts@cra.com
Research Institution
N/A
Abstract

A successful WMD terrorist attack against the United States would have profound and potentially catastrophic impact on our nation. Quick, efficient, and effective localization of radiological threats in unstructured environments is imperative to mitigate and deny such an event. Man-portable devices are used to localize radiological materials in unstructured environments, but manned detection is both costly and dangerous due to exposure and contamination risk requiring immediate decontamination to mitigate adverse and long-term health effects.
Real-time, detection, localization and mapping of radiological materials has applications ranging from nuclear decommissioning, waste management, and environmental remediation to emergency response, international safeguards, and homeland security. Man-portable radiation detectors have become smaller and more capable, and commercial unmanned aircraft systems (UAS) have become much cheaper and more sophisticated. Charles River Analytics has matured drone technologies with increased levels of autonomy using commercial off-the-shelf (COTS) sensors and drones enabling us to keep costs down while ensuring operators are out of harm's way.
Charles River Analytics proposes to develop a system for identifying radiological or nuclear (RAD/NUC) threats using COTS radiation detectors in combination with perceptual sensors on small drone(s) flying autonomously or semi-autonomously. The 3-D radiation localization and mapping payload (RADLAMP) is platform-agnostic and can be deployed on unmanned ground, or aerial vehicles, without the need for external power or offline processing. Using advanced computer vision/machine learning techniques, radiation detection, and autonomous navigation algorithms, the envisioned product extends our existing product lines and furthers the capabilities of relevant stakeholders in homeland security.

* Information listed above is at the time of submission. *

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