Cited by 399Robotics and Sensor-Based Localization3D Surveying and Cultural HeritageInertial Sensor and Navigation

The DOI matches its Crossref record; 13 of the 17 references it cites were found in a registry or an index.

Zebedee: Design of a Spring-Mounted 3-D Range Sensor with Application to Mobile Mapping

Bosse, M., Zlot, R., Flick, P.·2012·IEEE Transactions on Robotics

Abstract

Three-dimensional perception is a key technology for many robotics applications, including obstacle detection, mapping, and localization. There exist a number of sensors and techniques for acquiring 3-D data, many of which have particular utility for various robotic tasks. We introduce a new design for a 3-D sensor system, constructed from a 2-D range scanner coupled with a passive linkage mechanism, such as a spring. By mounting the other end of the passive linkage mechanism to a moving body, disturbances resulting from accelerations and vibrations of the body propel the 2-D scanner in an irregular fashion, thereby extending the device's field of view outside of its standard scanning plane. The proposed 3-D sensor system is advantageous due to its mechanical simplicity, mobility, low weight, and relatively low cost. We analyze a particular implementation of the proposed device, which we call Zebedee, consisting of a 2-D time-of-flight laser range scanner rigidly coupled to an inertial measurement unit and mounted on a spring. The unique configuration of the sensor system motivates unconventional and specialized algorithms to be developed for data processing. As an example application, we describe a novel 3-D simultaneous localization and mapping solution in which Zebedee is mounted on a moving platform. Using a motion capture system, we have verified the positional accuracy of the sensor trajectory. The results demonstrate that the six-degree-of-freedom trajectory of a passive spring-mounted range sensor can be accurately estimated from laser range data and industrial-grade inertial measurements in real time and that a quality 3-D point cloud map can be generated concurrently using the same data.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tro.2012.2200990

Cites

13 of 13 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 17 references

Research works printed but not linked: 2

  1. wulf, 2003, Fast 3D scanning methods for laser measurement systems, Proc Int Conf Control Syst Comput Sci, 312
  2. petrie, 2010, Mobile mapping systems: An introduction to the technology, GeoInformatics, 13, 32

Cited by

Sorted by citations

Items 201–300 of 399

Metadata

Authors
Bosse, M., Zlot, R., & Flick, P.
Affiliations
Commonwealth Scientific and Industrial Research Organisation (AU)
Venue
IEEE Transactions on Robotics
Published
2012-10
Volume
28
Issue
5
Pages
1104-1119
ISSN
  • 1552-3098 (ISSN-L)
  • 1941-0468
OpenAlex
W2054804188
Cited by
399
References
17
Citations by year
2026: 5 · 2025: 14 · 2024: 18 · 2023: 21 · 2022: 31 · 2021: 39 · 2020: 34 · 2019: 43 · 2018: 41 · 2017: 32 · 2016: 39 · 2015: 40 · 2014: 26 · 2013: 16
FWCI
44.13
Type
journal article
Language
en
Open access
closed
Locations
IEEE Transactions on Robotics (publishedVersion)
Funders
Commonwealth Scientific and Industrial Research Organisation
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
  • Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
  • Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
Keywords
inertial measurement unit, mobile mapping, SLAM, 3D point clouds, low-cost sensor design

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review