sukthankar-motion - Simulation &...

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Unformatted text preview: Simulation & Gaming DOI: 10.1177/1046878107309686 2008; 39; 64 Simulation Gaming Gita Sukthankar, Michael Mandel and Katia Sycara models Creating physically embodied agents using realistic human motion The online version of this article can be found at: Published by: On behalf of: Association for Business Simulation & Experiential Learning International Simulation & Gaming Association Japan Association of Simulation & Gaming North American Simulation & Gaming Association Society for Intercultural Education, Training, & Research can be found at: Simulation & Gaming Additional services and information for Email Alerts: Subscriptions: Reprints: Permissions: © 2008 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution. at UNIV OF CENTRAL FLORIDA on March 6, 2008 Downloaded from 64 AUTHORS’ NOTE: We would like to thank Jessica Hodgins, Moshe Mahler, and the Carnegie Mellon University Motion Capture Lab for their help during the data acquisition process. Rahul Sukthankar’s help proofreading this document was invaluable. This work was supported in part by Office of Naval Research Grant No. N000140210438, Air Force Office of Scientific Research Grant No. F496200110542, and International Technology Alliance Grant No. W911NF0630001. SIMULATION & GAMING, Vol. 39 No. 1, March 2008 64-82 DOI: 10.1177/1046878107309686 © 2008 Sage Publications Creating physically embodied agents using realistic human motion models Gita Sukthankar Carnegie Mellon University, USA Michael Mandel Apple Computer, USA Katia Sycara Carnegie Mellon University, USA Many simulations are populated with physically embodied agents capable of taking physical actions in the virtual world. Creating these agents, or virtual humans, is demanding; not only must the agents demon- strate visual verisimilitude, but they must plan and act in a way that is consistent with that of humans, espe- cially for training simulations in which the participants are attempting to learn real-world skills. This article discusses an approach for adapting agent decision-making techniques to accurately model the phys- ical capabilities of human subjects. To achieve this, the authors rely on human movement data acquired with a motion capture apparatus to build physically realistic models of human movement. To aid agents’ planning, the authors construct a physical capability model for the agents, an accurate estimate of the time required for a real human to perform various movement sequences. A cost map over the space of agent actions is calculated by creating and stochastically sampling motion graphs assembled from the human data exemplars. The agents can use this cost model during the planning process to select between equivalentexemplars....
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This note was uploaded on 08/25/2011 for the course EGN 3060c taught by Professor Sukthankar,g during the Fall '08 term at University of Central Florida.

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sukthankar-motion - Simulation &...

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