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Experimental Robotics pp 277–291Cite as

The Interactive Urban Robot IURO: Towards Robot Action in Human Environments

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Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 109))

Abstract

Spatial reasoning and semantic environment understanding is a fundamental ability of robots navigating in unstructured dynamic environments. Since spatial and semantic reasoning is tightly linked to the sensor perception information, it is desirable that it is directly integrated into the environment model. This paper presents the interplay of a novel environment representation called Semantic Rtree (SRTree) and Markov Logic Networks for reasoning. The SRTree is a semantic occupancy grid based on the hierarchical Rtree data structure that models the probability of occupancy of each grid cell and additionally assigns a class label to it. The main advantages of the proposed approach are (1) a hierarchical representation of large scale outdoor urban environments, which (2) captures both quantitative (metric) and qualitative (semantic) aspects of the environment and allows reasoning in a single data structure, and (3) the capability of dealing with higher-order spatial relations. The proposed methods are experimentally evaluated on a large scale 3D point cloud dataset of downtown Munich enhanced by RGB image data. The dataset is being made publicly available.

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Notes

  1. 1.

    http://alchemy.cs.washington.edu/.

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Acknowledgments

This work was supported in part by the ERC Advanced Grant project SHRINE (http://www.shrine-project.eu).

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Authors and Affiliations

  1. Institute of Automatic Control Engineering, Technische Universität München, Arcisstr. 21, 80290, Munich, Germany

    Dirk Wollherr, Sheraz Khan, Christian Landsiedel & Martin Buss

Authors
  1. Dirk Wollherr
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  2. Sheraz Khan
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  3. Christian Landsiedel
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  4. Martin Buss
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Corresponding author

Correspondence to Christian Landsiedel .

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Editors and Affiliations

  1. Drexel University, Philadelphia, Pennsylvania, USA

    M. Ani Hsieh

  2. Department of Computer Science, Stanford University, Stanford, California, USA

    Oussama Khatib

  3. Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Vijay Kumar

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Wollherr, D., Khan, S., Landsiedel, C., Buss, M. (2016). The Interactive Urban Robot IURO: Towards Robot Action in Human Environments. In: Hsieh, M., Khatib, O., Kumar, V. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 109. Springer, Cham. https://doi.org/10.1007/978-3-319-23778-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-23778-7_19

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