Learning Contact Locations for Pushing and Orienting Unknown Objects

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Date
2013-10Author
Hermans, Tucker
Li, Fuxin
Rehg, James M.
Bobick, Aaron F.
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Show full item recordAbstract
We present a method by which a robot learns to
predict effective contact locations for pushing as a function of
object shape. The robot performs push experiments at many
contact locations on multiple objects and records local and
global shape features at each point of contact. Each trial
attempts to either push the object in a straight line or to
rotate the object to a new orientation. The robot observes
the outcome trajectories of the manipulations and computes
either a push-stability or rotate-push score for each trial.
The robot then learns a regression function for each score
in order to predict push effectiveness as a function of object
shape. With this mapping, the robot can infer effective push
locations for subsequent objects from their shapes, regardless
of whether they belong to a previously encountered object class.
These results are demonstrated on a mobile manipulator robot
pushing a variety of household objects on a tabletop surface.