Modeling Physical Capabilities of Humanoid Agents Using Motion Capture Data

Gita Sukthankar, Michael Mandel, Katia Sycara and Jessica K. Hodgins
Conference Paper, Proceedings of Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 344 - 351, July, 2004

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Abstract

In this paper we demonstrate a method for fine-grained modeling of a synthetic agent’s physical capabilities—-running, jumping, sneaking, and other modes of movement. Using motion capture data acquired from human subjects, we extract a motion graph and construct a cost map for the space of agent actions. We show how a planner can incorporate this cost model into the planning process to select between equivalent goal-achieving plans. We explore the utility of our model in three different capacities: 1) modeling other agents in the environment; 2) representing heterogeneous agents with different physical capabilities; 3) modeling agent physical states (e.g., wounded or tired agents). This technique can be incorporated into applications where human-like, high-fidelity physical models are important to the agents’ reasoning process, such as virtual training environments.


@conference{Sukthankar-2004-8973,
author = {Gita Sukthankar and Michael Mandel and Katia Sycara and Jessica K. Hodgins},
title = {Modeling Physical Capabilities of Humanoid Agents Using Motion Capture Data},
booktitle = {Proceedings of Autonomous Agents and Multi-Agent Systems (AAMAS)},
year = {2004},
month = {July},
pages = {344 - 351},
keywords = {synthetic agents: human-like, lifelike, and believable agents},
} 2017-09-15T09:04:40-04:00