General Place Recognition Survey: Towards the Real-world Autonomy Age
- URL: http://arxiv.org/abs/2209.04497v1
- Date: Fri, 9 Sep 2022 19:37:05 GMT
- Title: General Place Recognition Survey: Towards the Real-world Autonomy Age
- Authors: Peng Yin, Shiqi Zhao, Ivan Cisneros, Abulikemu Abuduweili, Guoquan
Huang, Micheal Milford, Changliu Liu, Howie Choset, and Sebastian Scherer
- Abstract summary: The place recognition community has made astonishing progress over the last $20$ years.
Few methods have shown promising place recognition performance in complex real-world scenarios.
This paper can be a tutorial for researchers new to the place recognition community and those who care about long-term robotics autonomy.
- Score: 36.49196034588173
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Place recognition is the fundamental module that can assist Simultaneous
Localization and Mapping (SLAM) in loop-closure detection and re-localization
for long-term navigation. The place recognition community has made astonishing
progress over the last $20$ years, and this has attracted widespread research
interest and application in multiple fields such as computer vision and
robotics. However, few methods have shown promising place recognition
performance in complex real-world scenarios, where long-term and large-scale
appearance changes usually result in failures. Additionally, there is a lack of
an integrated framework amongst the state-of-the-art methods that can handle
all of the challenges in place recognition, which include appearance changes,
viewpoint differences, robustness to unknown areas, and efficiency in
real-world applications. In this work, we survey the state-of-the-art methods
that target long-term localization and discuss future directions and
opportunities.
We start by investigating the formulation of place recognition in long-term
autonomy and the major challenges in real-world environments. We then review
the recent works in place recognition for different sensor modalities and
current strategies for dealing with various place recognition challenges.
Finally, we review the existing datasets for long-term localization and
introduce our datasets and evaluation API for different approaches. This paper
can be a tutorial for researchers new to the place recognition community and
those who care about long-term robotics autonomy. We also provide our opinion
on the frequently asked question in robotics: Do robots need accurate
localization for long-term autonomy? A summary of this work and our datasets
and evaluation API is publicly available to the robotics community at:
https://github.com/MetaSLAM/GPRS.
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