MIT/Battelle Postdoctoral Associate
Department of Mechanical Engineering, Center for Ocean Engineering
Address: 77 Mass Ave, Bldg 5-223
I am currently a Battelle/MIT Postdoctoral Associate in the Laboratory for Autonomous Marine Sensing Systems headed by Henrik Schmidt. I completed my PhD in March of 2015 at MIT with Henrik Schmidt, with a thesis titled "Characterization of underwater target geometry from Autonomous Underwater Vehicle sampling of bistatic acoustic scattered fields". My primary research goal is to use autonomous underwater vehicles (AUVs) to investigate novel acoustic sensing and autonomy for defense and oceanography applications. Current research topics include:
- Using vehicle autonomy, signal processing, machine learning and target scattering acoustics to characterize seabed targets in real time on AUVs using data collected on simple nose arrays.
- Acoustic navigation for very low-cost AUVs.
- Vehicle autonomy using relative acoustic positioning for acoustic and oceanographic sensing applications.
- Multi-AUV autonomy for acoustic sensing.
- Oceanographic sensing using virtual arrays of AUVs
- Passive acoustic tracking
E. M. Fischell and H. Schmidt. “Supervised machine learning for estimation of target aspect angle from bistatic acoustic scattering.” IEEE JOE (Accepted for publication).
E. M. Fischell and H. Schmidt. “Environmental effects on seabed object bistatic scattering classification.” J. Acoust. Soc. Am. 141, 28-37 (2017).
E. M. Fischell and H. Schmidt. "AUV behaviors for collection of bistatic and multistatic acoustic scattering data from seabed targets." 2016 IEEE International Conference on Robotics and Automation (ICRA) 2016, pp 2645-2650.
E. M. Fischell and H. Schmidt, “Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.” J. Acoust. Soc. Am. 138, 3773-3784 (2015).
E. Fischell, T. Schneider and H. Schmidt, “Design, Implementation and Characterization of Precision Timing for Bistatic Acoustic Data Acquisition.” IEEE JOE, ISSN: 0364-9059 (2015).
Recent Conference Papers and Presentations
O. A. Viquez, E. M. Fischell , N. R. Rypkema and H. Schmidt, “Design of a general autonomy payload for low-cost AUV R D”, 2016 IEEE/OES Autonomous Underwater Vehicles (AUV), pp 151-155, (November 2016).
Erin M. Fischell and H. Schmidt. “Seabed target discrimination using multistatic acoustic scattering data”, Proceedings of Meetings on Acoustics, Honolulu HI, Nov. 2016.
E. M. Fischell, N. Rypkema and H. Schmidt. “Relative Acoustic Navigation for Sensing with Low-Cost AUVs.” ICRA 2016 Workshop on Marine Robot Localization and Navigation, May 20, 2016. (avail. http://icra2016.csail.mit.edu/navigation-localization-workshop/abstracts/05_Fischell_ICRAworkshop_abstract.pdf).
E. M. Fischell, H. Schmidt. “Estimation of cylinder orientation using autonomous underwater vehicle mapping of bistatic scattered fields.” Proceedings of Meetings on Acoustics, Jacksonville FL, November 2015.
E. M. Fischell, H. Schmidt. “Autonomous Assessment of Seabed Ripple Geometry from Bistatic Acoustic Scattering Data.” Seabed and Sediment Acoustics: Measurements and Modelling Conference, Bath, UK, Sept. 7-9 2015.
A. Anderson, E. Fischell, T. Howe, T. Miller, A. Parrales-Salinas, N. Rypkema, D. Barrett, M. Benjamin, A. Brennen, M. Defillipo, J. Leonard, L. Paull, H. Schmidt, N. Wang and A. Yaari. “An Overview of MIT-Olin's Approach in the AUVSI RobotX Competition.” Field and Service Robotics 2015.
E. M. Fischell, S. Petillo, T. Howe, H. Schmidt. “Mapping bistatic scattering from spherical and cylindrical targets using an autonomous underwater vehicle in BAYEX'14 experiment.” Presentation for the Acoustical Society of America, Indianapolis, Indiana, 27–31 October 2014.
E. M. Fischell and H. Schmidt. "Use of supervised machine learning for real-time classification of underwater targets using Autonomous Underwater Vehicle sampled bistatic acoustic scattered fields." Presentation for the Acoustical Society of America, Providence, RI, May 2014.
E. M. Fischell and H. Schmidt. "Supervised machine learning for estimation of rough bottom anisotropy direction using bistatic acoustic scattered fields." Presentation for the Acoustical Society of America, San Francisco CA, November 2013.
E. M. Fischell and H. Schmidt. "Supervised machine learning for classification of underwater target geometry from sampled scattered acoustic fields in the presence of rough bottom interference." Presentation for the Acoustical Society of America, Kansas City Missouri, 2012.
E. M. Fischell and H. Schmidt. "Supervised machine learning for real time classification of underwater targets from sampled scattered acoustic fields." Presentation for the Acoustical Society of America, San Diego CA, 2011.
Erin Fischell, Tracy Cheung, Brian Mittereder, James Brian Rajsky and Peter Sullivan. "Flexible Mission Infrastructure for Autonomous Underwater Vehicles." Conference Proceedings for AUVSI’s Unmanned Systems North America 2009, Washington DC, August 2009.