This Major Research Instrumentation (MRI) project will develop a multi-sensor system that will allow measurements from moving platforms, such as remotely connected/remotely paired unmanned vehicles or drones. The novel instrument will be used for real-time calibration of specialty cameras in a novel computer-vision system. This new knowledge and technique will enhance public safety through rapid and accurate inspection of critical infrastructure and large-scale physical systems. This instrumentation will contribute to fundamental research at the University of Massachusetts-Lowell and the development of new curriculum on sensors integration, controls, and machine-vision. Collaborations with local high school teachers will introduce K-12 students to computer-vision and unmanned aerial vehicle (UAV) inspection, encouraging them to pursue STEM careers.

This potentially transformative instrumentation will be used for real-time calibration of stereophotogrammetry and remotely paired digital cameras, thereby streamlining calibration procedures and enabling measurements from moving platforms. The multi-sensor system records the orientation angles and the relative distance between two paired cameras needed to triangulate the 3D position of optical targets with respect to the cameras? retinal plane. This obviates the need for time-consuming calibration and fixed sensor positioning and has the potential to enlarge the field of view. The instrumentation will provide a new means for recording data to inform and validate ongoing advanced modeling efforts and to enable a new understanding of large-scale systems? dynamic characteristics. Research using this instrumentation will drive a fundamental understanding of how physical parameters such as displacement, deformation, and strain characterize the behavior of large-scale systems like large infrastructure, wind turbine blades and parachutes.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2020-09-01
Budget End
2022-08-31
Support Year
Fiscal Year
2020
Total Cost
$455,096
Indirect Cost
Name
University of Massachusetts Lowell
Department
Type
DUNS #
City
Lowell
State
MA
Country
United States
Zip Code
01854