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Onboard Sensemaking for Guidance, Control, and Remote Sensing Application in...
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Onboard Sensemaking for Guidance, Control, and Remote Sensing Application in Image Processing

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 4254

Special Issue Editor

Prof. Dr. Jonathan Black

E-Mail Website
Guest Editor
Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
Interests: space systems; advanced lightweight aerospace structures; autonomous vehicles; advanced sensing technology; novel orbital analysis

Special Issue Information

Dear Colleagues,

The upcoming explosion in the number of small satellites in orbit and unmanned systems in the air requires the implementation of onboard, autonomous image processing for a broad range of applications, including sensemaking, change detection, rendezvous and docking, autonomous inspection, navigation, swarming, and prediction. Simultaneously, advancements in devices and networks are rapidly increasing sensor output, processing, and fusion capabilities, such that it is becoming possible to envision extremely large mesh networks of heterogeneous platforms and sensors in all operational domains: sea, land, air, space, and cyberspace.

This Special Issue aims to explore all types of imaging sensors, fusion, and onboard sensemaking algorithms for autonomous unmanned systems in the air and in space.

Prof. Dr. Jonathan Black
Guest Editor

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

  • image processing
  • onboard processing
  • sensor fusion
  • heterogenous sensor networks
  • all-domain sensors
  • sensemaking

Published Papers (1 paper)

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Research

37 pages, 9764 KiB  
Article
ReS2tAC—UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices
by Boitumelo Ruf, Jonas Mohrs, Martin Weinmann, Stefan Hinz and Jürgen Beyerer
Sensors 2021, 21(11), 3938; https://doi.org/10.3390/s21113938 - 7 Jun 2021
Cited by 7 | Viewed by 3665
Abstract
With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs were the only processing hardware that were capable of high-performance computing, while at the same time preserving [...] Read more.
With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs were the only processing hardware that were capable of high-performance computing, while at the same time preserving a low power consumption, essential for embedded systems. However, the recently increasing availability of embedded GPU-based systems, such as the NVIDIA Jetson series, comprised of an ARM CPU and a NVIDIA Tegra GPU, allows for massively parallel embedded computing on graphics hardware. With this in mind, we propose an approach for real-time embedded stereo processing on ARM and CUDA-enabled devices, which is based on the popular and widely used Semi-Global Matching algorithm. In this, we propose an optimization of the algorithm for embedded CUDA GPUs, by using massively parallel computing, as well as using the NEON intrinsics to optimize the algorithm for vectorized SIMD processing on embedded ARM CPUs. We have evaluated our approach with different configurations on two public stereo benchmark datasets to demonstrate that they can reach an error rate as low as 3.3%. Furthermore, our experiments show that the fastest configuration of our approach reaches up to 46 FPS on VGA image resolution. Finally, in a use-case specific qualitative evaluation, we have evaluated the power consumption of our approach and deployed it on the DJI Manifold 2-G attached to a DJI Matrix 210v2 RTK unmanned aerial vehicle (UAV), demonstrating its suitability for real-time stereo processing onboard a UAV. Full article
(This article belongs to the Special Issue Onboard Sensemaking for Guidance, Control, and Remote Sensing Application in Image Processing)
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