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Sign Understanding in Support of Autonomous Navigation (SUSAN)

Award Information

Department of Defense
Defense Advanced Research Projects Agency
Award ID:
Program Year/Program:
2003 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Charles River Analytics Inc.
MA Cambridge, MA 02138-4555
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 2
Fiscal Year: 2003
Title: Sign Understanding in Support of Autonomous Navigation (SUSAN)
Agency / Branch: DOD / DARPA
Contract: DAAH0103CR196
Award Amount: $375,642.00


Mobile robots currently cannot detect and read arbitrary signs. Existing work on road sign recognition is template based, limiting the detectable signs to a specific set. This is a major hindrance to mobile robot usability, since they cannot be taskedusing directions that are intuitive to humans. It also limits their ability to report their position relative to intuitive landmarks.We propose to develop a system for Sign Understanding in Support of Autonomous Navigation (SUSAN), that detects signs from various cues common to signs (vivid colors, compact shape, text or other symbols) and from contextual cues (placement with respect toroads, walls, doors, poles, etc.). In Phase II, we will enhance our Phase I color and text-based sign detection and add adaptation for a variety of lighting and background conditions (both indoors and outdoors). Our partial 3D scene modeling module willbias detectors to specific parts of the scene based on shape from motion, 3D line extraction, vertical surface and vanishing point detection. Our tracking module will accumulate evidence from tracking potential signs in time. We will demonstrateperformance on an indoor mobile robot and, in collaboration with PercepTek, we will demonstrate SUSAN on the MARS unmanned ground vehicle.

Principal Investigator:

Magnus Snorrason
Principal Scientist

Business Contact:

Paul Gonsalves
Vice President
Small Business Information at Submission:

625 Mount Auburn Street Cambridge, MA 02138

EIN/Tax ID: 042803764
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No