SBIR-STTR Award

This SBIR Phase I project proposes a probabilistic approach to determine a vehicles location using onboard video sensors and foundational map data. The system does not rely on only one type of information source, instead it combines proposals from a variety of location estimators to find a vehicles location in GPS-denied environments. The system takes advantage of recent advancements in computer vision-based technologies and automated sensor exploitation and machine learning to exploit onboard sensor data and identify cues to geo-locate itself. The Phase I effort will include: development of location estimation framework, development of location estimator modules using reference maps and video features, development of a probabilistic fusion module, quantitative and qualitative evaluation of the technologies, and demonstration of proof of concept using real-world data from multiple scenarios.

This SBIR Phase II project proposes a probabilistic approach to determine a vehicle’s location using onboard video and Lidar sensors and foundation map data in GPS denied environments. The proposed system does not rely on only one type of information source, instead it combines proposals from a variety of location estimators to find a vehicles location in GPS-denied environments. The system takes advantage of recent advancements in computer vision-based technologies and automated sensor exploitation and machine learning to exploit onboard sensor data and identify cues to geolocate itself. The Phase II effort will focus towards improving Phase I technologies and transitioning them into a prototype system on Novateur’s robotic platform. The Phase II effort will leverage Novateur Team’s expertise in the areas of sensor data exploitation, geolocation in GPS denied environment, deep learning and convolutional neural network, and image and scene understanding.