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Daniel Helmick's Picture
Jet Propulsion Laboratory
M/S 82-105
4800 Oak Grove Drive
Pasadena, CA 91109
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Member of:
Robotic Mobility Group
Daniel Helmick
Member of Technical Staff
(Short description>>)

Daniel Helmick received his B.S degree in Mechanical Engineering from Virginia Polytechnic Institute and State University and his M.S. in Mechanical Engineering with a specialization in controls from Georgia Institute of Technology in 1996 and 1999 respectively. Since June 1999 he has been working at the Jet Propulsion Laboratory on robotics research projects involving vision/sensor based control of robots, state estimation, and navigation and mobility algorithms. He has worked on robotic vehicles covering a wide range of functionality, including: Mars research rovers for rough terrain mobility; small, tracked robots for urban mobility; a cryobot for ice penetration; and reconfigurable wheeled robots for Mars exploration. His research interests include: sensor-based control of robots, sensor fusion and state estimation, and rover navigation and mobility.

Mechanical Engineering B.S., Virginia Tech 1996

Mechanical Engineering M.S., Georgia Tech, 1999

- Mars Science Laboratory (MSL) Flight Software Team Sample Acquisition/Sample Processing and Handling (SA/SPaH) Subsystem developing software to control various parts of the SA/SPaH subsystem

- Remote Terrain Classification and Terrain-Adaptive Navigation led a
team that developed technologies for Mars rover navigation in rough terrain
including online learning algorithms for predicting slip using mast mounted
cameras, integrated with a path planning algorithm and a slip-compensated path following algorithm

- Mars Science Laboratory Manipulation Technology (Focused Technology Program) developed algorithms and strategies for sample acquisition and handling for a 2009 mission to Mars, including force sensing and control algorithms to enable collection of rock cores with a robotic arm

- Navigation on Slopes led a team of researchers on a Mars Technology Program
project; addressed the problem of Mars rover mobility and navigation on steep,
sandy slopes; used a vision based pose estimation technique (Visual Odometry)
merged with traditional inertial/dead reckoning techniques, implemented with a
Kalman filter; end result was a slip compensation/path following algorithm; tested this algorithm in multiple scenarios, including a week long field-test in the Mojave desert

- Cryobot designed and implemented control system for an ice boring robot
designed for in-situ science of Earth/Mars/Europa ice; aided in a successful field test of vehicle on a glacier in Svalbard, Norway

- DARPA TMR implemented high-speed, autonomous stair climbing algorithm
with a physics-based control algorithm and a Kalman filter to fuse vision and
inertial data for a tracked vehicle used for urban reconnaissance; aided the
development of a 6 DOF Kalman filter pose estimation algorithm

- AXEL ground up mechanical, electrical, and systems design of a novel reconfigurable mobile robot

- Automated Material Transport aided development of a vision-based
autonomous docking algorithm; used a geometric-model-based pose refinement
algorithm for estimating the pose of fork lift pallets

- Rocky 8 mechanical lead on a Mars Technology rover development platform
used for research in navigation, path planning, etc.

Flight Project and Research Task Involvement

Flight Projects:
2011 - Mars Science Laboratory

Research Tasks:
Multi-Sensor Terrain Classification and Terrain-Adaptive Navigation for Rovers in Very Rough Terrain
Rover-based Manipulation Technology
Small Body Surface Sampler and Explorer (SmalBoSSE)

sensor-based control of robots
sensor fusion and state estimation
rover mobility and navigation

NASA Technical Excellence Award, Cryobot Team, May 2002.

2007 "Best Paper Award" Robotics Society of Japan Advanced Robotics Journal paper: "Slip-Compensated Path Following for Planetary Exploration Rovers"

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