Shape Reconstruction Using Active Tactile Sensors
Mark Moll. Shape Reconstruction Using Active Tactile Sensors. Ph.D. Thesis, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, 2002.
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Abstract
We present a new method to reconstruct the shape of an unknown object using tactile sensors, without requiring object immobilization. Instead, sensing and nonprehensile manipulation occur simultaneously. The robot infers the shape, motion and center of mass of the object based on the motion of the contact points as measured by the tactile sensors. This allows for a natural, continuous interaction between manipulation and sensing. We analyze the planar case first by assuming quasistatic dynamics, and present simulation results and experimental results obtained using this analysis. We extend this analysis to the full dynamics and prove observability of the nonlinear system describing the shape and motion of the object being manipulated. In our simulations, a simple observer based on Newton's method for root finding performs really well. Using the same framework we can also describe the shape and dynamics of three-dimensional objects. However, there are some fundamental differences between the planar and three-dimensional case, due to increased tangent dimensionality. Also, perfect global shape reconstruction is impossible in the 3D case, but it is almost trivial to obtain upper and lower bounds on the shape. The 3D shape reconstruction method has also been implemented and we present some simulation results.
BibTeX Entry
@PhdThesis{moll2002:shape-recon-using-activ,
author = "Mark Moll",
title = "Shape Reconstruction Using Active Tactile Sensors",
school = "Computer Science Department, Carnegie Mellon University",
year = 2002,
address = "Pittsburgh, PA",
month = jul,
keywords = "tactile sensing, shape reconstruction, nonprehensile
manipulation",
abstract = "We present a new method to reconstruct the shape of an
unknown object using tactile sensors, without requiring
object immobilization. Instead, sensing and nonprehensile
manipulation occur simultaneously. The robot infers the
shape, motion and center of mass of the object based on
the motion of the contact points as measured by the
tactile sensors. This allows for a natural, continuous
interaction between manipulation and sensing. We analyze
the planar case first by assuming quasistatic dynamics,
and present simulation results and experimental results
obtained using this analysis. We extend this analysis to
the full dynamics and prove observability of the nonlinear
system describing the shape and motion of the object being
manipulated. In our simulations, a simple observer based
on Newton's method for root finding performs really
well. Using the same framework we can also describe the
shape and dynamics of three-dimensional objects. However,
there are some fundamental differences between the planar
and three-dimensional case, due to increased tangent
dimensionality. Also, perfect global shape reconstruction
is impossible in the 3D case, but it is almost trivial to
obtain upper and lower bounds on the shape. The 3D shape
reconstruction method has also been implemented and we
present some simulation results.",
}