Mark Moll :: publications

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.",
}

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