Aaron M. Johnson

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A System for Multi-Step Mobile Manipulation: Architecture, Algorithms, and Experiments

International Symposium on Experimental Robotics, October, 2016. To Appear.

Siddhartha Srinivasa, Aaron M. Johnson, Gilwoo Lee, Michael C. Koval, Shushman Choudhury, Jennifer E. King,
Christopher M. Dellin, Matthew Harding, David T. Butterworth, Prasanna Velagapudi, and Allison Thackston*
Robotics Institute, Carnegie Mellon University
* Toyota Motor Engineering & Manufacturing North America

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Abstract
       Household manipulation presents a challenge to robots because it requires perceiving a variety of objects, planning multi-step motions, and recovering from failure. This paper presents practical techniques that improve performance in these areas by considering the complete system in the context of this specific domain. We validate these techniques on a table-clearing task that involves loading objects into a tray and transporting it. The results show that these techniques improve success rate and task completion time by incorporating expected real-world performance into the system design.
This work was supported by the Toyota Motor Corporation.
BibTeX entry
@inproceedings{paper:srinivasa_iser_2016,
   author = {Siddhartha S. Srinivasa and Aaron M. Johnson and Gilwoo Lee and 
             Michael C. Koval and Shushman Choudhury and Jennifer E. King and
             Christopher M. Dellin and Matthew Harding and David T. Butterworth and 
             Prasanna Velagapudi and Allison Thackston},
   title = {A System for Multi-Step Mobile Manipulation: Architecture, Algorithms, and Experiments},
   booktitle = {International Symposium on Experimental Robotics},
   year = {2016},
   month = {October},
   address= {Tokyo, Japan},
   note = {To appear.}
}