Probabilistic Human Action Prediction and Wait-sensitive Planning for Responsive Human-robot Collaboration

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Date
2013-10Author
Hawkins, Kelsey P.
Vo, Nam
Bansal, Shray
Bobic, Aaron F.
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Show full item recordAbstract
A novel representation for the human component of multi-step,
human-robot collaborative activity is presented. The goal of the system is to
predict in a probabilistic manner when the human will perform different
subtasks that may require robot assistance. The representation is a graphical
model where the start and end of each subtask is explicitly represented as a
probabilistic variable conditioned upon prior intervals. This formulation
allows the inclusion of uncertain perceptual detections as evidence to drive
the predictions. Next, given a cost function that describes the penalty for
different wait times, we develop a planning algorithm which selects
robot-actions that minimize the expected cost based upon the distribution
over predicted human-action timings. We demonstrate the approach in assembly
tasks where the robot must provide the right part at the right time depending
upon the choices made by the human operator during the assembly.