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Deceptive robot motion: synthesis, analysis and experiments

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Abstract

Much robotics research explores how robots can clearly communicate true information. Here, we focus on the counterpart: communicating false information, or hiding information altogether—in one word, deception. Robot deception is useful in conveying intentionality, and in making games against the robot more engaging. We study robot deception in goal-directed motion, in which the robot is concealing its actual goal. We present an analysis of deceptive motion, starting with how humans would deceive, moving to a mathematical model that enables the robot to autonomously generate deceptive motion, and ending with a studies on the implications of deceptive motion for human-robot interactions and the effects of iterated deception.

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Authors and Affiliations

  1. The Robotics Institute, Carnegie Mellon University, Pittsburgh, USA

    Anca Dragan, Rachel Holladay & Siddhartha Srinivasa

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  1. Anca Dragan
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  2. Rachel Holladay
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  3. Siddhartha Srinivasa
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Corresponding author

Correspondence to Rachel Holladay.

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This is one of several papers published in Autonomous Robots comprising the “Special Issue on Robotics Science and Systems”.

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Dragan, A., Holladay, R. & Srinivasa, S. Deceptive robot motion: synthesis, analysis and experiments. Auton Robot 39, 331–345 (2015). https://doi.org/10.1007/s10514-015-9458-8

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  • DOI: https://doi.org/10.1007/s10514-015-9458-8

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