The Stingray Project
I'm the Principal Investigator for Stingray, a Phase II SBIR project
funded by the US Army Tank-Automotive Research, Development,
and Engineering Center (TARDEC).
The goal of this research project is to develop techniques for
high-speed teleoperation of small unmanned ground vehicles (UGVs).
Thousands
of small UGVs, like the iRobot PackBot, have been deployed overseas,
where they are helping soldiers deal with improvised explosive devices
(IEDs) and other threats. However, in order to be useful in a
wider range of missions, such as high-tempo infantry operations, small
UGVs will need to operate at much higher speeds.
For the
Stingray Project, we are taking a prototype of iRobot's next-generation
Warrior x700 UGV, and modifying it for high speed operation. In order
to control small UGVs at high speeds, new teleoperation techniques are
required. Stingray will combine immersive teleoperation with
semi-autonomous driver assist behaviors.
We are working with Chatten Associates
to integrate their Head-Aimed Remote Viewer (HARV) to the Stingray
Warrior UGV. The HARV combines a head-tracking system with a
head-mounted display and a remote gimbaled camera. The camera
tracks every motion of the operator's head, providing the illusion of
being in the vehicle, and greatly increasing situational awareness.
In
addition, we will add semi-autonomous behaviors that will help the
operator control the Stingray Warrior at high speeds. These
behaviors will allow the operator to issue high-level directives to the
UGV, such as "maintain this heading" or "follow this street", freeing
the operator from needing to control every move the vehicle makes.
This will allow the operator to search the environment for
potential threats, while the UGV autonomously controls low-level
vehicle motions. These behaviors will also allow the UGV to
maintain a stable speed and heading, even when driving at high speed
over rough terrain.
This video
shows our initial experiments using the HARV to drive the prototype
Warrior and a high-speed surrogate UGV (a modified, gas-powered R/C car
used for testing) through a slalom course.
Stingray Video
The Daredevil Project
I'm also the Principal Investigator for Daredevil, a Phase II SBIR project funded by TARDEC. The goal of the
project is to use ultra wideband (UWB) radar sensors to allow small UGVs
(like the iRobot PackBot) to navigate through foliage (tall grass,
forests, jungles) and adverse weather (rain, snow, dust) while avoiding
obstacles.
Most autonomous robots
use sensors such as vision or laser rangefinders (LIDAR) to detect
obstacles. While these sensors work well to detect solid obstacles
in open space, they typically are not able to differentiate a solid
object (which the robot needs to steer around) from foliage such as
tall grass (which the robot can push through). One of the primary
goals of this project is to use UWB radars to see through foliage and
to be able to differentiate between solid objects (such as people,
rocks, or vehicles) and vegetation.
Our initial results have been very promising. The first image
below shows a person (Mike) in a field of tall grass, barely visible to
human eyesight. The second image shows the UWB radar data, which
clearly detects Mike through the vegetation.
The Wayfarer Project
I was the Principal Investigator for the TARDEC-funded Wayfarer Project, a
two-year, $1.3 million effort to develop autonomous urban navigation
capabilities for man-portable mobile robots, such as the iRobot PackBot.
We equipped two Wayfarer PackBot prototypes with stereo vision and LIDAR to
perform autonomous reconnaissance missions in urban terrain, including
GPS-denied areas. The new ruggedized Wayfarer navigation payload
is shown above left, and a 3D map generated by the Instant Scene
Modeler (iSM) during perimeter reconnaissance is shown above
right. (iSM was developed by Stephen Se at MDA Corporation
and was integrated with Wayfarer at iRobot
Corporation.)
Wayfarer Videos
Previous Research
View the robots I've developed in my Robot Gallery.
I've previously conducted research and
development in mobile robotics at:
While at the Naval
Research Laboratory, I developed frontier-based
exploration, a technique that allows mobile robots to explore and
map unknown environments.
Selected Publications
Daredevil:
Ultra Wideband Radar Sensing for Small UGVs
Brian Yamauchi, Proceedings of SPIE
Vol. 6561: Unmanned Systems Technology IX, Orlando, FL, April
2007
Autonomous
Urban Reconnaissance Using Man-Portable UGVs
Brian Yamauchi, Proceedings of SPIE
Vol. 6230: Unmanned Systems Technology VIII, Orlando, FL, April
2006
Wayfarer: An Autonomous Navigation Payload
for the PackBot
Brian
Yamauchi, Proceedings of AUVSI
Unmanned Vehicles North America 2005, Baltimore, MD, June 2005
The
Wayfarer Modular Navigation Payload for Intelligent Robot Infrastructure
Brian Yamauchi, Proceedings of SPIE
Vol. 5804: Unmanned Ground Vehicle Technology VII, Orlando, FL, March
2005
Griffon: A Man-Portable Hybrid
UGV/UAV
Brian Yamauchi and Pavlo Rudakevych, Industrial
Robot, Vol. 31, No. 5, pp. 443-450, 2004
PackBot:
A Versatile Platform for Military Robotics
Brian Yamauchi, Proceedings of SPIE
Vol. 5422: Unmanned Ground Vehicle Technology VI, Orlando, FL,
April 2004
Integrating
Exploration and Localization for Mobile Robots
Brian Yamauchi, Alan Schultz, and William
Adams, Adaptive Behavior, Vol. 7, No. 2, Spring 2000
Mobile Robot
Exploration and Map-Building with Continuous Localization
Brian Yamauchi, Alan Schultz, and William
Adams, Proceedings of the 1998 IEEE International Conference on
Robotics and Automation, Leuven, Belgium, May 1998, pp. 3715-3720
Frontier-Based
Exploration Using Multiple Robots
Brian Yamauchi, Proceedings of the
Second International Conference on Autonomous Agents (Agents '98),
Minneapolis, MN, May 1998, pp. 47-53
A
Frontier-Based Approach for Autonomous Exploration
Brian Yamauchi, Proceedings of the
1997 IEEE International Symposium on Computational Intelligence in
Robotics and Automation, Monterey, CA, July 1997, pp. 146-151
Place Recognition in
Dynamic Environments
Brian Yamauchi and Pat Langley, Journal
of Robotic Systems, Special Issue on Mobile Robots, Vol. 14, No. 2,
February 1997, pp. 107-120
Spatial Learning for Navigation in Dynamic
Environments
Brian Yamauchi and Randall Beer, IEEE
Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics,
Special Issue on Learning Autonomous Robots, Vol. 26, No. 3, June 1996,
pp. 496-505
iRobot
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