Carnegie Mellon University
The
Pose estimation for planar contact manipulation with manifold particle filters

Michael Koval, Nancy Pollard , and Siddhartha Srinivasa
International Journal of Robotics Research, Vol. 34, No. 7, pp. 922-945, June, 2015.


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Abstract
We investigate the problem of using contact sensors to estimate the pose of an object during planar pushing by a fixed-shape hand. Contact sensors are unique because they inherently discriminate between “contact” and “no-contact” configurations. As a result, the set of object configurations that activates a sensor constitutes a lower-dimensional contact manifold in the configuration space of the object. This causes conventional state estimation methods, such as the particle filter, to perform poorly during periods of contact due to particle starvation. In this paper, we introduce the manifold particle filter as a principled way of solving the state estimation problem when the state moves between multiple manifolds of different dimensionality. The manifold particle filter avoids particle starvation during contact by adaptively sampling particles that reside on the contact manifold from the dual proposal distribution. We describe three techniques, one analytical and two sample-based, of sampling from the dual proposal distribution and compare their relative strengths and weaknesses. We present simulation results that show that all three techniques outperform the conventional particle filter in both speed and accuracy. In addition, we implement the manifold particle filter on a real robot and show that it successfully tracks the pose of a pushed object using commercially available tactile sensors.

Keywords
tactile sensing, pose estimation, manipulation under uncertainty, non-prehensile manipulation

Notes
Sponsor: DARPA, NASA, NSF, and the Toyota Motor Corporation
Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Personal Robotics

Text Reference
Michael Koval, Nancy Pollard , and Siddhartha Srinivasa, "Pose estimation for planar contact manipulation with manifold particle filters," International Journal of Robotics Research, Vol. 34, No. 7, pp. 922-945, June, 2015.

BibTeX Reference
@article{Koval_2015_7952,
   author = "Michael Koval and Nancy {Pollard } and Siddhartha Srinivasa",
   title = "Pose estimation for planar contact manipulation with manifold particle filters",
   journal = "International Journal of Robotics Research",
   pages = "922-945",
   publisher = "SAGE",
   month = "June",
   year = "2015",
   volume = "34",
   number = "7",
}