Rapid automated damage detection with autonomous robots (RAD²AR)

Northeastern University

Northeastern University

pacific northwest economic region



This project is funded in part by:

National Science Foundation United States Department of homeland securityXSEDE

Northeastern University    PNWER

The authors thank S. Singh, S. Scherer, D. Huber, B. Akinci, and N. Michael of Carnegie Mellon University; K. Coleman and M. MacNeil of Northeastern University; M. Clifford at DGT Associates, Inc.; and Faro Technologies for their contributions to this research.

This material is based upon work supported in part by the National Science Foundation under Grant No. IIS-1328816.  This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation under Grant No. ACI-1548562.  We thank D. J. Choi for his assistance with optimizing the simulation software used in this research, which was made possible through the XSEDE Extended Collaborative Support Service (ECSS) program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.