articleIEEE Transactions on RoboticsDec 1, 2016GREEN OA

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age

CCCesar CadenaLCLuca CarloneHCHenry CarrilloYLYasir LatifDSDavide Scaramuzza

ETH Zurich · Massachusetts Institute of Technology · +6 more institutions

Indexed inarxivcrossref

Abstract

Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications and witnessing a steady transition of this technology to industry. We survey the current state of SLAM and consider future directions. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance…

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Authors

8
  • CC
    Cesar CadenaCorresponding

    ETH Zurich

  • LC
    Luca Carlone

    Massachusetts Institute of Technology, Decision Systems (United States)

  • HC
    Henry Carrillo

    Pontificia Universidad Javeriana, Sergio Arboleda University

  • YL
    Yasir Latif

    University of Adelaide

  • DS
    Davide Scaramuzza

    University of Zurich

Topics & keywords

Keywords
  • Robustness (evolution)
  • Robotics
  • Simultaneous localization and mapping
  • Robot
  • Scalability
  • Metric (unit)
  • Position paper
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