sensors-logo

Journal Browser

Journal Browser

Multi-Sensor and Multi-Modal Place Localization

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: closed (10 March 2023) | Viewed by 4378

Special Issue Editors


E-Mail Website
Guest Editor
School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
Interests: computer vision; machine learning; robotics

E-Mail Website
Guest Editor
School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
Interests: 3D reconstruction; camera calibration

Special Issue Information

Dear Colleagues,

Emergent technologies such as autonomous driving and augmented reality require reliable and accurate localization solutions. For this purpose, exteroceptive sensors (such as cameras, LiDAR, and RADAR) have demonstrated their effectiveness for relative and absolute pose estimation in a scene. Recently, visual localization techniques have greatly benefited from the rise of deep learning through novel approaches for image retrieval, pose regression, 3D registration, and deep keypoint matching. Despite this significant progress, many use-cases and challenges remain to be addressed, such as noise, illumination, and viewpoint invariance. Under these adverse conditions, long-term localization would significantly benefit from the use of multimodal sensors. However, computer vision solutions specifically designed for multisensory platforms remain poorly investigated. Furthermore, other applications, such as multi-agent localization, have so far attracted little attention despite considerable practical implications. In this context, we are pleased to invite researchers to present novel solutions targeting the limitations of the current visual localization strategies.

This Special Issue of Sensors aims to collect review articles and original research papers in the field of place localization with an emphasis on multisensory data. Potential topics include but are not limited to the following:

  • Visual localization
  • multisensor localization
  • multimodal localization
  • Hierarchical localization
  • Geolocalization
  • Pose estimation
  • Keypoint matching
  • Structure from Motion
  • Simultaneous Localization and Mapping
  • 3D registration

Prof. Dr. In So Kweon
Prof. Dr. Francois Rameau
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

23 pages, 17641 KiB  
Article
MAV Localization in Large-Scale Environments: A Decoupled Optimization/Filtering Approach
by Abanob Soliman, Hicham Hadj-Abdelkader, Fabien Bonardi, Samia Bouchafa and Désiré Sidibé
Sensors 2023, 23(1), 516; https://doi.org/10.3390/s23010516 - 3 Jan 2023
Viewed by 3085
Abstract
Developing new sensor fusion algorithms has become indispensable to tackle the daunting problem of GPS-aided micro aerial vehicle (MAV) localization in large-scale landscapes. Sensor fusion should guarantee high-accuracy estimation with the least amount of system delay. Towards this goal, we propose a linear [...] Read more.
Developing new sensor fusion algorithms has become indispensable to tackle the daunting problem of GPS-aided micro aerial vehicle (MAV) localization in large-scale landscapes. Sensor fusion should guarantee high-accuracy estimation with the least amount of system delay. Towards this goal, we propose a linear optimal state estimation approach for the MAV to avoid complicated and high-latency calculations and an immediate metric-scale recovery paradigm that uses low-rate noisy GPS measurements when available. Our proposed strategy shows how the vision sensor can quickly bootstrap a pose that has been arbitrarily scaled and recovered from various drifts that affect vision-based algorithms. We can consider the camera as a “black-box” pose estimator thanks to our proposed optimization/filtering-based methodology. This maintains the sensor fusion algorithm’s computational complexity and makes it suitable for MAV’s long-term operations in expansive areas. Due to the limited global tracking and localization data from the GPS sensors, our proposal on MAV’s localization solution considers the sensor measurement uncertainty constraints under such circumstances. Extensive quantitative and qualitative analyses utilizing real-world and large-scale MAV sequences demonstrate the higher performance of our technique in comparison to most recent state-of-the-art algorithms in terms of trajectory estimation accuracy and system latency. Full article
(This article belongs to the Special Issue Multi-Sensor and Multi-Modal Place Localization)
Show Figures

Figure 1

Back to TopTop