학술논문

Machine Vision for Obstacle Avoidance, Tripwire Detection, and Subsurface Radar Image Correction on a Robotic Vehicle for the Detection and Discrimination of Landmines
Document Type
Conference
Source
2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring), 2019. :1602-1606 Jun, 2019
Subject
Bioengineering
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Geoscience
Photonics and Electrooptics
Radar imaging
Springs
Cameras
Robot vision systems
Landmine detection
Language
ISSN
1559-9450
Abstract
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.