Planning Coordinated Event Observation for Structured Narratives

Dylan A. Shell, Li Huang, Aaron Becker, Jason M. O'Kane
In Proc. IEEE International Conference on Robotics and Automation 2019.

Abstract

This paper addresses the problem of using autonomous robots to record events that obey narrative structure. The work is motivated by a vision of robot teams that can, for example, produce individualized highlight videos for each runner in a large-scale road race such as a marathon. We introduce a method for specifying the desired structure as a function that describes how well the captured events can be used to produce an output that meets the specification. This function is specified in a compact, legible form similar to a weighted finite automaton. Then we describe a planner that uses simple predictions of future events to coordinate the robots' efforts to capture the most important events, as determined by the specification. We describe an implementation of this approach, and demonstrate its effectiveness in a simulated race scenario both in simulation and in a hardware testbed.

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@inproceedings{SheHua+19,
  author       = {Dylan A. Shell and Li Huang and Aaron Becker and Jason M.
		 O'Kane},
  title        = {Planning Coordinated Event Observation for Structured
		 Narratives},
  booktitle    = {Proc. IEEE International Conference on Robotics and
		 Automation},
  year	       = {2019}
}

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