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Daniel Clouse's Picture
Address:
Jet Propulsion Laboratory
M/S 125-209
4800 Oak Grove Drive
Pasadena, CA 91109
Phone:
818.354.1157
Fax:
818.393.0879
Email:
Member of:
347J
Maritime and Aerial Perception Systems Group
Daniel Clouse
Member of Technical Staff
(Short description>>)

Daniel Clouse finished his BA in Computer Science from UC Berkeley in 1982. He worked at NCR Corporation, Systems Engineering, San Diego from 1982 to 1992 as a Principal Programmer / Analyst in the Programming Languages Department. He designed and developed a number of code generators and run-time systems on Unix 486 platform for C++, COBOL, NCRL, Ada. As a project leader, he supervised 4 programmers, and received 2 technical merit awards.He finished his PhD in Cognitive Science and Computer Science at UC San Diego in 1998. His PhD dissertation uses recurrent neural networks and statistics derived from large text corpora to model human performance on finding the meanings of words.
As an intern at JPL in the summer of 1996, he developed a statistical method for improving the accuracy of the Grid Algorithm for star identification, allowing a small field of view science camera to be used as a star tracker.He started full-time at JPL in 1999 working on the Mars Sample Return Project. During this period, he contributed to a number of trade and feasibility studies on how to rendezvous with an orbiting sample canister in Mars orbit, including feasibility of IR detector, feasibility of lidar, design of corner cube placement for sample canister, estimation of maximum detection distance of sample canister using lidar. The last two of these studies were supported by diffraction simulation software he designed and developed.In 2001, he started on the LAMP (Laser Mapper) Project which sought to develop a space-qualifiable scanning laser ranging system. Early on in this project, he developed algorithms for interpreting lidar range maps to accurately find the position of a spherical sample canister in Mars orbit. Later, he took on the role of Technical Lead and principal designer of LAMP OS (operating system) software
. He supervised a team of 4 software engineers to develop, document, and test a
pproximately 30K lines of code, including lidar drivers, scanner control, task monitoring, inter-task communication, space-craft communication, and graphical us
er interface functions.
In 2003, he began on the "Driving on Slopes" task which produced an algorithm to allow rovers to deal with slippage while driving on sloped surfaces. This is i
n support of the 2009 Mars Smart Lander project. He is responsible for the impl
ementation of forward and inverse kinematics, for continuous real-time control o
f steering and driving of the 6 steerable wheel locomotion system, and for collection, interpretation, and reaction to real-time sensor data including stereo cameras, IMU, and joint angles. In 2007, for the High Fidelity Traversibility Anal
ysis task, he developed a path planning algorithm which chooses a low-energy path via simulation in ROAMS.In 2004, he started as task lead of the System Development and Evaluation task o
f the JADE project. JADE developed and evaluated autonomous target recognition algorithms for use in satellite imagery. Daniels task was responsible for evaluating those algorithms and for performing trade studies on alternative hardware
platforms required to allow fast performance.
In late 2005, Daniel implemented and evaluated the Relative Affine Depth target tracking algorithm for the Single Cycle Instrument Placement task, and improved the data collection process for the validation of the GESTALT algorithm for the Navigation Valiation task.In 2005 through 2009, he was the software lead on the Autonomous Aerobot task, a
nd served on the ground operations crew. He developed a new software architectu
re for state estimation and locomotion, wrote and tuned new actuator and navigation controllers, and added new sensors (cameras, barometric altimeter, anemometer).

In 2006 and 2007, he developed a reuseable camera interface for the CLARAty task.

In 2007 through 2009, he improved the imaging capabilities of the Angel Fire persistent surveillance platform. He was responsibile for integrating JPL software into the existing Angel Fire system, for testing and for coordinating deliveries of new software. New capabilities included dead pixel elimination, vignetting reduction, dewarping, ground camera calibration, and on-the-fly fine camera calibration. In 2009, he developed a real-time feature tracking algorithm for improved image stabilization and geo-registration.

In 2008, for the USSV project, he wrote feature tracking code for camera stabilization, and wrote code to predict the ocean surface plane from IMU measurements.

In 2008 and 2009, he worked on the AEGSE project (Mars Science Laboratory motor controllers). He cleaned up the existing telemetry code, and added functionality for user-defineable error handling.

1982 BA Computer Science, UC Berkeley
1992 MS Computer Science, UC San Diego
1992 PhD Cognitive Science & Computer Science, UC San Diego

1982-92 NCR Corp. Systems Engineering, San Diego.
Principal Programmer/Analyst
Programming Languages Dept.

1992-99 UC San Diego, CSE Dept.
Various Research/Teaching Assistentships, Lecturer

1999-now Jet Propulsion Lab
Machine Vision Group
Senior Member Technical Staff

Computer Vision
Machine Learning
Cognitive Science - word sense disambiguation, language translation

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