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Award Abstract #0521675

spacer MRI: Development of an Autonomous Robotic Vehicle Instrument (ARVIN)

NSF Org: CNS
Division of Computer and Network Systems
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Initial Amendment Date: July 15, 2005
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Latest Amendment Date: April 14, 2011
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Award Number: 0521675
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Award Instrument: Standard Grant
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Program Manager: Rita V. Rodriguez
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering
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Start Date: October 1, 2005
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Expires: March 31, 2012 (Estimated)
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Awarded Amount to Date: $376,021.00
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Investigator(s): Gabriel Elkaim elkaim@soe.ucsc.edu (Principal Investigator)
Jorge Cortes (Co-Principal Investigator)
William Dunbar (Co-Principal Investigator)
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Sponsor: University of California-Santa Cruz
1156 High Street
SANTA CRUZ, CA 95064-1077 (831)459-5278
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NSF Program(s): MAJOR RESEARCH INSTRUMENTATION,
COMPUTING RES INFRASTRUCTURE
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Program Reference Code(s): 9135, 9178, 9218, 9251, HPCC
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Program Element Code(s): 1189, 7359

ABSTRACT
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This project, developing a platform for research and training to serve as an instrument for evaluating robotic subsystem and supersystem performance, accelerates and enhances the evolution of autonomous vehicle subsystems and component parts by providing a baseline instrument to measure and assess the performance and capabilities of the various portions of a given autonomous vehicle design. This Autonomous Robotic Vehicle Instrument (ARVIN) is designed to allow simultaneous, parallel operation of multiple instruments, actuators, and software/hardware subsystems. Due to the common environment in which the items are operating, the ARVIN yields a precise, robust metric of comparative performance and capability of the item in question. Inherently rapidly reconfigurable by design of its network-centric architecture, the ARVIN enables quick, easy substitutions and augmentations of sensors and actuators on the evaluation platform; it is not a set of identical robot structures that join and reform to move or climb.

The ARWIN tests, simulates, and validates subsystems and components in three tightly coupled hierarchical areas acknowledge as critical to advances in robotics vehicles:

-Guidance, Navigation, and Control (GNC),

-Sensor and Actuators Suites, and

-Software and Network Architectures.

The Autonomous Robotic Vehicle Instrument consists of an Argo Conquest 6x6 Off-road/Amphibious vehicle, heavily modified, and a Hardware-in-the-Loop (HIL) simulator for the vehicle. The vehicle will be fitted with ultrasonic sonar and SICK LiDAR for collision avoidance, fiber optic gyros, IMU's, and NavCom STARFIRE differential GPS receivers for guidance, a Pentium class PC-104 stack with high speed communication networks for control, and a Videre MEGA-STC-VAR stereoscopic high speed color camera for vision capture.

In general, due to the incredibly high cost (in time and money) of constructing an autonomous vehicle of any kind, designs are rarely modified unless the mission cannot be completed by the original vehicle design. Very rarely are the initial trade-off studies revisited and explored to see what might have been done differently. Thus, the ARVIN should have profound impact on the kind of trade-off studies that most autonomous vehicle design programs have to-date been missing.

Broader Impact: ARVIN allows students and researchers to gain experience on an actual, physical, autonomous rover. This kind of practical training in systems integration, sensor fusion, software architecture for real-time systems, and actual control systems implementations has much to offer. The Naval Postgraduate School and the Intelligent Robotics Group (IRG) at NASA-Ames has indicated interest and enthusiasm in collaborating and experimenting with the modular chassis that will result of the ARVIN. Contributing to further understand trade-offs for mobile robotics, the platforms will also be used for outreach. The ARVIN infrastructure should become a cost-effective general robotics toll that may be easily replicated at other institutions.


PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

(Showing: 1 - 10 of 17)
  Show All

J. Connors and G. H. Elkaim. "Manipulating b-spline based paths for obstacle avoidance in autonomous ground vehicles," Proceedings of the Institute of Navigation National Technical Meeting, 2007, 2007, p. 1081.

Choi, J., Elkaim, G.. "Bzier Curves for Trajectory Guidance," World Congress on Engineering and Computer Science, 2008.

Connors, J., and Elkaim, G.. "Trajectory Generation and Control Methodology for an Autonomous Ground Vehicle," AIAA Guidance, Navigation and Control Conference, 2008.

Lizarraga, M., Elkaim, G.. "Spatially Deconflicted Path Generation for Multiple UAVs in a Bounded Airspace," ION/IEEE Position, Location, and Navigation Symposium, 2005, p. 633.

Choi, J., Curry, R., and Elkaim, G.. "Collision Free Real-Time Motion Planning for Omnidirectional Vehicles," Proceedings of the European Control Conference (ECC 2009), 2009.

Lizarraga, M., Dobrokhodov, V., Elkaim, G., Curry, R., and Kaminer, I.. "Simulink Based H
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