Cited by 162Robot Manipulation and LearningSensor Technology and Measurement SystemsSoft Robotics and Applications

Proximity Perception in Human-centered Robotics: A Survey on Sensing Systems and Applications

Open access
Navarro, Stefan Escaida, Muhlbacher-Karrer, Stephan, Alagi, Hosam, Zangl, Hubert, Koyama, Keisuke, Hein, Bjorn, Duriez, Christian, Smith, Joshua R.·2022·IEEE Transactions on Robotics

Abstract

Proximity perception is a technology that has the potential to play an essential role in the future of robotics. It can fulfill the promise of safe, robust, and autonomous systems in industry and everyday life, alongside humans, as well as in remote locations in space and underwater. In this survey article, we cover the developments of this field from the early days up to the present, with a focus on human-centered robotics. In this domain, proximity sensors are typically deployed in two scenarios: first, on the exterior of manipulator arms to support safety and interaction functionality, and second, on the inside of grippers or hands to support grasping and exploration. Therefore, based on this observation, in the beginning of this article, we propose a categorization to organize the use cases of proximity sensors in human-centered robotics. Then, we devote effort to present the sensing technologies and different measuring principles that have been developed over the years, also providing a summary in form of a table. Following, we review the literature regarding the applications that have been proposed. Finally, we give an overview of the most important trends that will shape the future of this domain.

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.2021.3111786

Cites

145 of 145 references verified0 citation errors · 0 not checkable

Statistics

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?

  • Low level fast reactive control has been explored for integration with robot manipulators in proximity perception and visual servoing.

    “Low level fast reactive control has been explored for integration with robot manipulators in proximity perception (Mayton et al., 20102010; Navarro et al., 2021) as well as visual servoing (Espiau et al., 1992).”

    From Lessons for Robotics From the Control Architecture of the Octopus (2022) · cites this paper as Navarro et al., 2021

Self-check

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

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

Cites

Part of this paper’s reference list could not be split into single entries.

Flagged first, then by citations

Research works printed but not linked: 2

  1. [1][1] T. Zhou, M. Yang, K. Jiang, H. Wong, and D. Yang, 'MMW radarbased technologies in autonomous driving: A review,' Sensors , vol. 20, no. 24, p. 7283, 2020. -
  2. [26][26] A. Hoffmann, A. Poeppel, A. Schierl, and W. Reif, 'Environmentaware proximity detection with capacitive sensors for human-robotinteraction,' in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2016, pp. 145-150. -

Cited by

Sorted by citations

Authors
Navarro, S. E., Muhlbacher-Karrer, S., Alagi, H., Zangl, H., Koyama, K., Hein, B., Duriez, C., & Smith, J. R.
Affiliations
  • Centre Inria de l'Université de Lille (FR)
  • JOANNEUM RESEARCH ROBOTICS, Institute for Robotics and Mechatronics, Klagenfurt, Austria
  • Karlsruhe Institute of Technology (DE)
  • University of Klagenfurt (AT)
  • The University of Osaka (JP)
  • Institute for Anthropomatics and Robotics - Intelligent Process Automation and Robotics Lab (IAR-IPR), Karlsruhe Institute of Technology, Karlsruhe, Germany
  • Inria Lille—Nord Europe, Villeneuve d’Ascq, France
  • University of Washington (US)
Venue
IEEE Transactions on Robotics
Published
2022-06
Volume
38
Issue
3
Pages
1599-1620
ISSN
  • 1552-3098 (ISSN-L)
  • 1941-0468
OpenAlex
W3138748647
Cited by
162
References
145
Citations by year
2026: 38 · 2025: 37 · 2024: 38 · 2023: 29 · 2022: 18 · 2021: 2
FWCI
9.68
Type
journal article
Language
en
Open access
Locations
  • IEEE Transactions on Robotics (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • HAL (submittedVersion, cc-by)
  • LillOA (Université de Lille (University Of Lille)) (submittedVersion, other-oa)
  • arXiv (Cornell University) (cc-by)
Funders
  • Region Hauts-de-France (ANR-17-ERC2-0029)
  • European Regional Development Fund (26616/30969/44253)
  • Karntner Wirtschaftsforderungsfonds
  • Bundesministerium für Bildung und Forschung (V5ARA114)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
  • Physical Sciences › Computer Science › Computer Networks and Communications › Sensor Technology and Measurement Systems
  • Physical Sciences › Engineering › Biomedical Engineering › Soft Robotics and Applications
Keywords
human-centered robotics, proximity sensors, human-robot interaction, robot safety, robot manipulators, robotic hand, grasping, sensor technology, human-robot collaboration

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