Skip Navigation


Curtis Padgett


4800 Oak Grove Drive
M/S 198-235

Pasadena, CA 91109

Member of:

347J - Perception Systems

Curtis Padgett

Group Supervisor


Curtis Padgett the Supervisor for the Maritime and Aerial Perception Systems Group. He completed his doctoral work in pattern recognition while working at JPL. His interests include computer vision, structure from motion, automated calibration, pattern classification, star identification and machine learning.


Ph.D. Computer Science, University California, San Diego 1997
M.S. Computer Science, University California, San Diego 1993
B.S. The Evergreen State College Olympia, WA 1991

Professional Experience

Task Manager for DARPA Robotic Autonomy in Complex Environments with Resiliency (RACER) 2021-current:

This task is to develop off-road autonomous driving of a ground vehicle at near human performance.

Engineering Lead for Quantifying Uncertainty and Kinematics of Earth Systems Imager QUAKES (2019-2021):

This NASA task designs and implents visible and SWIR sensors in an array for deployment aboard a Gulf Stream jet in order to develop highly accurate 3D geo-rectified terrain data using Structure from Motion.

Task Manager and PI for Cross Usv Stereo/Vertical Integrated Passive EO Ranger (2016-2019):

This ONR task designs and implents next generation on water passive sensing that looks to reduce weight and power, improve range estimation, cover a wider angular area, and significantly reduce costs.

Task Manager and PI Sea Hunter II & III (2016-2020):

This Leidos (ONR) task is to mature path planning, mission execution and passive sensing (MUSE) for deployment on Sea Hunter. The three elements have been developed (save for the path planner) outside of the DARPA ACTUV program and the tasks involves integrating the component technologies and in the case of the path planner, developing additional capabilities.

Task Manager and PI Mechanically Uncoupled Stereo EO (MUSE) (2015-current):

This ONR-Leidos task is to provide a very wide baseline stereo capability for medium and larger USVs. The task is developing on line calibration of imagery for non-coupled, simultaneously captured imagery on the water surface. This sensor system will be delivered to Sea Hunter (Navy robotic vessel) for on water testing.

Task Manager and JPL PI-Collaboartive Operations in Denied Environment (2015-2017):

This task is to provide LEIDOS (DARPA prime) with a mapping and image based localization algorithm that enables accurate positioning in a GPS denied environment for a heterogeneous composition of UAVs.

JPL Principal Investigator- Anti-Submarine Warfare Continuous Trail Unmanned Vessel (September 2012-2017):
This task will apply JPL robotic control and planning technology to support a long duration robotic mission for an unmanned surface vehicle with the capability to track submarines.

JPL Principal Investigator- Autonomous Aerial Cargo/Utility System (September 2012-2014):
This task will apply image processing and hazard classification algorithms to understand landing site uncertainty for a vertical takeoff and landing system.

Principal Investigator- BlueDevil (April 2012-2014):
This task is a continuation of JPL image processing for wide area surveillance activities. In particular, this task will provide flight code for onboard gyro calibration for an image array and a step stare system. We will integrate an EKF to improve geo-registration capabilities.

Principal Investigator- Aerial Processing for AV(September 2011-2012):

Task Manager and Co-Investigator- SRTD: Exploitation of Aerial Imagery (September 2010-current):
This task is a 3 year effort to improve JPL capabilities in exploitation of aerial imagery.

Principal Investigator- 3D Structure from ScanEagle Imagery (July 2010-2012)

Principal Investigator- JPL Angel Fire Project (July 2006-April 2012)

Research Interests

Pattern Recognition
Advanced Computing Systems
Machine Vision


  1. T. Pham, W. Seto, S. Daftry, A. Brinkman, J. Mayo, C. Padgett, E. Kulczycki, R. Detry, "Rover Localization for Tube Pickup: Dataset, Methods and Validation for Mars Sample Return Planning," IEEE Aerospace Conference, Big Sky, MT, USA, 05 February 2020.
  1. C. Padgett, K. Kreutz-Delgado, and S. Udomkesmalee, "Evaluation of Star Identification Techniques," Journal of Guidance, Control, and Dynamics, 20(2), 01 March 1997.