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Multispectral, Polarized and Unconventional Vision in Robotics
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Multispectral, Polarized and Unconventional Vision in Robotics

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

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 6884

Special Issue Editors

Dr. Julien R Serres

E-Mail Website
Guest Editor
The Institute of Mouvement Sciences – Etienne-Jules Marey, Aix Marseille University, ISM UMR7287, 13009 Marseille, France
Interests: biorobotics; bio-inspired robotics; optic flow; visual guidance; celestial compass; polarization-based localization; bio-inspired navigation
Special Issues, Collections and Topics in MDPI journals
Dr. Olivier Morel

E-Mail Website
Guest Editor
ImViA, Laboratory, University of Bourgogne, 71200 Le Creusot, France
Interests: polarimetric cameras; polarimetric imagery; bio-inspired imagery; attitude estimation; omnidirectional vision; polarization-based localization; autonomous robotics
Dr. Pierre-Jean Lapray

E-Mail Website
Guest Editor
The Institute for Research in Computer Science, Mathematics, Automation and Signal, IRIMAS UR 7499, University of Haute-Alsace, 68100 Mulhouse, France
Interests: real-time imaging; high dynamic range imaging; polarization imaging; spectral imaging; filter array imaging: from sensor to pre-processing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Laurent Bigué

E-Mail Website
Guest Editor
The Institute for Research in Computer Science, Mathematics, Automation and Signal, IRIMAS UR 7499, University of Haute-Alsace, 68100 Mulhouse, France
Interests: polarimetry; optical engineering; diffraction; image processing; digital holography signal, image and video processing; LCD; polarimeter; optics

Special Issue Information

Dear Colleagues,

Vision in robotics can benefit from unconventional techniques such as multispectral or polarization imaging, or a combination of them. It is well known that animals such as birds, fish, crustaceans, or insects are capable of navigating over great distances, showing their abilities to exploit all visual information available in their terrestrial, aerial, or aquatic surrounding environment. They can manage this without detecting artificial signals coming from antennas or satellites, simply using polarization information. As a result, understanding how they detect and fuse visual information could be helpful in the development of innovative and disruptive technologies in autonomous robotics.     

Furthermore, despite advances in computer vision and the increase in pixel number or frame rate, it seems that current visual systems or devices available on the market, even based on unconventional techniques, do not reach the level of performance of the ones in animals’ visual system.

This Special Issue will bring together original and innovative works on visual information extraction from imaging or non-imaging techniques including unconventional visual sensors. Method papers describing optical test benches or calibration procedures will be also accepted.

Dr. Julien R Serres
Dr. Olivier Morel
Dr. Pierre-Jean Lapray
Prof. Dr. Laurent Bigué
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.

Keywords

  • polarized vision
  • unconventional visual sensors
  • multispectral imaging
  • omnidirectional vision
  • bio-inspired vision
  • celestial navigation
  • skylight navigation
  • polarization navigation
  • data fusion
  • computational imaging
  • optical device calibration
  • multi-visual and multi-modal sensor navigation system

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Published Papers (3 papers)

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Research

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17 pages, 2566 KiB  
Article
Measurement Modeling and Performance Analysis of a Bionic Polarimetric Imaging Navigation Sensor Using Rayleigh Scattering to Generate Scattered Sunlight
by Zhenhua Wan, Kaichun Zhao, Haoyuan Cheng and Peng Fu
Sensors 2024, 24(2), 498; https://doi.org/10.3390/s24020498 - 13 Jan 2024
Cited by 2 | Viewed by 1373
Abstract
The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and [...] Read more.
The bionic polarimetric imaging navigation sensor (BPINS) is a navigation sensor that provides absolute heading, and it is of practical engineering significance to model the measurement error of BPINS. The existing BPINSs are still modeled using photodiode-based measurements rather than imaging measurements and are not modeled systematically enough. This paper proposes a measurement performance analysis method of BPINS that takes into account the geometric and polarization errors of the optical system. Firstly, the key error factors affecting the overall measurement performance of BPINS are investigated, and the Stokes vector-based measurement error model of BPINS is introduced. Secondly, based on its measurement error model, the effect of the error source on the measurement performance of BPINS is quantitatively analyzed using Rayleigh scattering to generate scattered sunlight as a known incident light source. The numerical results show that in angle of E-vector (AoE) measurement, the coordinate deviation of the principal point has a greater impact, followed by grayscale response inconsistency of CMOS and integration angle error of micro-polarization array, and finally lens attenuation; in degree of linear polarization (DoLP) measurement, the grayscale response inconsistency of CMOS has a more significant impact. This finding can accurately guide the subsequent calibration of BPINS, and the quantitative results provide an important theoretical reference for its optimal design. Full article
(This article belongs to the Special Issue Multispectral, Polarized and Unconventional Vision in Robotics)
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14 pages, 3845 KiB  
Article
Skylight Polarization Pattern Simulator Based on a Virtual-Real-Fusion Framework for Urban Bionic Polarization Navigation
by Qianhui Li, Liquan Dong, Yao Hu, Qun Hao, Jiahang Lv, Jie Cao and Yang Cheng
Sensors 2023, 23(15), 6906; https://doi.org/10.3390/s23156906 - 3 Aug 2023
Cited by 3 | Viewed by 1897
Abstract
In a data-driven context, bionic polarization navigation requires a mass of skylight polarization pattern data with diversity, complete ground truth, and scene information. However, acquiring such data in urban environments, where bionic polarization navigation is widely utilized, remains challenging. In this paper, we [...] Read more.
In a data-driven context, bionic polarization navigation requires a mass of skylight polarization pattern data with diversity, complete ground truth, and scene information. However, acquiring such data in urban environments, where bionic polarization navigation is widely utilized, remains challenging. In this paper, we proposed a virtual-real-fusion framework of the skylight polarization pattern simulator and provided a data preparation method complementing the existing pure simulation or measurement method. The framework consists of a virtual part simulating the ground truth of skylight polarization pattern, a real part measuring scene information, and a fusion part fusing information of the first two parts according to the imaging projection relationship. To illustrate the framework, we constructed a simulator instance adapted to the urban environment and clear weather and verified it in 174 urban scenes. The results showed that the simulator can provide a mass of diverse urban skylight polarization pattern data with scene information and complete ground truth based on a few practical measurements. Moreover, we released a dataset based on the results and opened our code to facilitate researchers preparing and adapting their datasets to their research targets. Full article
(This article belongs to the Special Issue Multispectral, Polarized and Unconventional Vision in Robotics)
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Review

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45 pages, 50054 KiB  
Review
Passive Polarized Vision for Autonomous Vehicles: A Review
by Julien R. Serres, Pierre-Jean Lapray, Stéphane Viollet, Thomas Kronland-Martinet, Antoine Moutenet, Olivier Morel and Laurent Bigué
Sensors 2024, 24(11), 3312; https://doi.org/10.3390/s24113312 - 22 May 2024
Cited by 1 | Viewed by 2610
Abstract
This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals [...] Read more.
This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals do? How should polarization images be related to the physical properties of reflecting surfaces in the context of scene understanding? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying future directions in passive polarized vision for robotics. After an introduction, three key interconnected areas will be covered in the following sections: embedded polarization imaging; polarized vision for robotics navigation; and polarized vision for scene understanding. We will then discuss how polarized vision, a type of vision commonly used in the animal kingdom, should be implemented in robotics; this type of vision has not yet been exploited in robotics service. Passive polarized vision could be a supplemental perceptive modality of localization techniques to complement and reinforce more conventional ones. Full article
(This article belongs to the Special Issue Multispectral, Polarized and Unconventional Vision in Robotics)
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