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Yumi Iwashita

Address:

4800 Oak Grove Drive
M/S 198-219

Pasadena, CA 91101

Member of:

347P - Aerial and Orbital Image Analysis

Yumi Iwashita

Member of Technical Staff

Biography

Yumi Iwashita is a researcher in the Maritime and Aerial Perception Systems Group at JPL. Her research focuses on computer vision for robotics and Intelligence, Surveillance, and Reconnaissance (ISR) applications. Prior to joining JPL, she was an Associate Professor at Kyushu University in Japan. She received her Ph.D. from the Graduate School of Information Science and Electrical Engineering, Kyushu University.

Education

- Ph.D. from the Graduate School of Information Science and Electrical Engineering, Kyushu University, Japan
- M.S. from the Graduate School of Information Science and Electrical Engineering, Kyushu University, Japan

Professional Experience

- Associate Professor, Kyushu University, Japan (2014-2016)
- Assistant Professor, Kyushu University, Japan (2007-2014)
- Postdoctoral Fellow, Imperial College London, UK (2007)

Research Interests

Computer vision for robotics and Intelligence, Surveillance, and Reconnaissance (ISR) applications. People tracking and 3D geometrical modeling using laser range finders. Experience with motion capture system using multiple cameras and people tracking system using cameras. Biometrics and pattern recognition for security systems, such as people recognition on both ground and aerial surveillance cameras. Range data processing for building a huge-scale structure with multiple robots.

Publications

2021
  1. E. Schaler, J. Wisnowski, Y. Iwashita, J. Edlund, J. Sly, W. Raff, K. Kriechbaum, M. Frost, R. McCormick, and J. Townsend, "Two-Stage Calibration of a 6-Axis Force-Torque Sensor for Robust Operation in the Mars 2020 Robot Arm," Advanced Robotics 35, no. 21-22 (2021): 1347-1358, 31 May 2021.
2020
  1. M. Ono, B. Rothrock, K. Otsu, Y. Iwashita, A. Didier, T. Islam, V. Sun, C. Laporte, K. Stack, S. Higa, J. Sawoniewicz, S. Daftry, C. Mattmann, V. Timmaraju, S. Sahnoune, O. Lamarre, D. Qiu, S. Ghosh, S. Nomura, H. Sarabu, S. Suehr, L. Folsom, G. Hedrick, H. Park, H. Roy, "MAARS: Machine Learning-Based Analytics for Rover Systems," IEEE Aerospace Conference, Big Sky, MT, USA, 05 February 2020.