4 February 2013 Multidisciplinary unmanned technology teammate (MUTT)
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Proceedings Volume 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques; 86620N (2013); doi: 10.1117/12.2010713
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
The U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) held an autonomous robot competition called CANINE in June 2012. The goal of the competition was to develop innovative and natural control methods for robots. This paper describes the winning technology, including the vision system, the operator interaction, and the autonomous mobility. The rules stated only gestures or voice commands could be used for control. The robots would learn a new object at the start of each phase, find the object after it was thrown into a field, and return the object to the operator. Each of the six phases became more difficult, including clutter of the same color or shape as the object, moving and stationary obstacles, and finding the operator who moved from the starting location to a new location. The Robotic Research Team integrated techniques in computer vision, speech recognition, object manipulation, and autonomous navigation. A multi-filter computer vision solution reliably detected the objects while rejecting objects of similar color or shape, even while the robot was in motion. A speech-based interface with short commands provided close to natural communication of complicated commands from the operator to the robot. An innovative gripper design allowed for efficient object pickup. A robust autonomous mobility and navigation solution for ground robotic platforms provided fast and reliable obstacle avoidance and course navigation. The research approach focused on winning the competition while remaining cognizant and relevant to real world applications.
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Nenad Uzunovic, Anne Schneider, Alberto Lacaze, Karl Murphy, Mark Del Giorno, "Multidisciplinary unmanned technology teammate (MUTT)", Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 86620N (4 February 2013); doi: 10.1117/12.2010713; http://dx.doi.org/10.1117/12.2010713
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KEYWORDS
Robotics

Cameras

Computer vision technology

Machine vision

Tablets

Human-machine interfaces

Bone

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