Our partnership with Carnegie Mellon University’s (CMU) Robotics Institute integrates ChemImage’s near real-time-capable imaging technology into a robotic platform that is evaluated for on-the-move detection capabilities.

Can we make smarter, threat-detection robots or apply our analytical capabilities to mobile, rather than fixed, solutions?  That’s the question at the heart our partnership with CMU — to evaluate our imaging technology performance when enabled with algorithms for near real-time, on-the move autonomous detection.

Working with ChemImage sample data as a baseline, CMU is leading experiments, road testing, and evaluations of a mobile sensor vehicle under a wide range of lighting conditions on different road types. They are also working concurrently on image reconstruction and lighting invariant algorithms (shadow detection and removal, normalizing sunlit and cloudy images, etc.) under different sensor sampling rates. 

The feedback we receive from CMU testing will help us explore features can help “re-train” ChemImage sensors with longer wavelength detections.  Meaning? 

Truly mobile threat detection is taking one step closer to science fact rather than fiction.