pub_tr.bib

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@techreport{delapuente11dense,
  author = {Paloma de la Puente and Andrea Censi},
  title = {Dense map inference with user-defined priors: from priorlets to scan eigenvariations},
  institution = {California Institute of Technology},
  number = {CaltechCDSTR:2011.002},
  year = {2011},
  pdf = {http://resolver.caltech.edu/CaltechCDSTR:2011.002},
  kind = {unref}
}

@incollection{scrapper09,
  author = {Scrapper, C. and Madhavan, R. and Lakaemper, R. and Censi, A. and Godil, A. and Wagan, A. and Jacoff, A.},
  affiliation = {The MITRE Corporation, 22102 McLean, VA USA},
  title = {Quantitative Assessment of Robot-Generated Maps},
  booktitle = {Performance Evaluation and Benchmarking of Intelligent Systems},
  editor = {Madhavan, Raj and Tunstel, Edward and Messina, Elena},
  publisher = {Springer US},
  isbn = {978-1-4419-0492-8},
  keyword = {Computer Science},
  pages = {221-248},
  pdf = {http://dx.doi.org/10.1007/978-1-4419-0492-8_10},
  note = {10.1007/978-1-4419-0492-8_10},
  abstract = {Mobile robotic mapping is now considered to be a sufficiently mature field with demonstrated successes in various domains. While much progress has been made in the development of computationally efficient and consistent mapping schemes, it is still murky, at best, on how these maps can be evaluated. We are motivated by the absence of an accepted standard for quantitatively measuring the performance of robotic mapping systems against user-defined requirements. It is our belief that the development of standardized methods for quantitatively evaluating existing robotic technologies will improve the utility of mobile robots in already established application areas, such as vacuum cleaning, robot surveillance, and bomb disposal. This approach will also enable the proliferation and acceptance of such technologies in emerging markets. This chapter summarizes our preliminary efforts by bringing together the research community towards addressing this important problem which has ramifications not only from researchers’ perspective but also from consumers’, robot manufacturers’, and developers’ viewpoints.},
  year = {2009},
  kind = {unref}
}

@techreport{censi06comparison,
  author = {Andrea Censi},
  title = {A comparison of algorithms for likelihood approximation 
             in Bayesian localization},
  institution = {Sapienza Universit\'a di Roma},
  year = {2006},
  url = {http://purl.org/censi/2006/ghtv},
  pdf = {http://purl.org/censi/research/2006-draft-acomparison.pdf},
  kind = {unref}
}

@misc{BaCa04,
  author = {Bahadori, S. and Calisi, D. and Censi, A. and Farinelli, A. and Grisetti, G. and Iocchi, L. and Nardi, D.},
  title = {Intelligent Systems for Search and Rescue},
  howpublished = {Proc. of IROS Workshop ``Urban Search and Rescue: from RoboCup to real world applications'' (IROS), Sendai, Japan},
  year = {2004},
  pdf = {http://www.dis.uniroma1.it/~calisi/papers/iros04rescue.pdf},
  kind = {unref}
}