NDLI: Attaining situational awareness for sliding autonomy

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Attaining situational awareness for sliding autonomy

Content Provider	ACM Digital Library
Author	Simmons, Reid Sellner, Brennan P. Hiatt, Laura M. Singh, Sanjiv
Abstract	We are interested in the problems of a human operator who is responsible for rapidly and accurately responding to requests for help from an autonomous robotic construction team. A difficult aspect of this problem is gaining an awareness of the requesting robot's situation quickly enough to avoid slowing the whole team down. One approach to speeding the initial acquisition of situational awareness is to maintain a buffer of data, and play it back for the human when their help is needed. We report here on an experiment to determine how the composition and length of this buffer affect the human's speed and accuracy in our multi-robot construction domain. The experiments show that, for our scenario, 5 - 10 seconds of one raw video feed led to the fastest operator attainment of situational awareness, while accuracy was maximized by viewing 10 seconds of three video feeds. These results are necessarily specific to our scenario, but we feel that they indicate general trends which may be of use in other situations. We discuss the interacting effects of buffer composition and length on operator speed and accuracy, and draw several conclusions from this experiment which may generalize to other scenarios.
Starting Page	80
Ending Page	87
Page Count	8
File Format	PDF
ISBN	1595932941
DOI	10.1145/1121241.1121257
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2006-03-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Case study Situational awareness Sliding autonomy User study
Content Type	Text
Resource Type	Article

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