Machine Vision for Obstacle Avoidance, Tripwire Detection, and Subsurface Radar Image Correction on a Robotic Vehicle for the Detection and Discrimination of Landmines

In a joint project, research partners across institutions combined specialties to develop a remotely-operable, multi-sensor, robotic device for the detection of land mines, unexploded ordnance (UXO), and improvised explosive devices (IEDs). The robotic detection device uses a novel subsurface radar...

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Bibliographic Details
Published in2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) pp. 1602 - 1606
Main Authors Bartolini, A., Bossi, L., Capineri, L., Falorni, P., Bulletti, A., Dimitri, M., Pochanin, G., Ruban, V., Ogurtsova, T., Crawford, F., Bechtel, T., Sallai, G., Kuske, A., Sinton, J., Truskavetsky, S., Byndych, T.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2019
Subjects
Cameras
Landmine detection
Radar imaging
Robot vision systems
Springs
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Summary:In a joint project, research partners across institutions combined specialties to develop a remotely-operable, multi-sensor, robotic device for the detection of land mines, unexploded ordnance (UXO), and improvised explosive devices (IEDs). The robotic detection device uses a novel subsurface radar with imaging and target classification to differentiate between dangerous landmines and harmless clutter. One important aspect of this project has been to develop a system for imaging the terrain and potential obstacles ahead of the moving vehicle. Three important tasks drive the need for this look-ahead imaging: obstacle avoidance, tripwire detection, holographic subsurface radar (HSR) image correction.
ISSN:2694-5053
DOI:10.1109/PIERS-Spring46901.2019.9017574