sensors-logo

Journal Browser

Journal Browser

Vision-Based and LiDAR-Based Navigation Systems for Spacecraft and Autonomous Vehicles

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

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 2523

Special Issue Editors


E-Mail Website
Guest Editor
Dipartimento di Ingegneria Industriale DII, University of Padova, Via Venezia, 1, 35121 Padova, Italy
Interests: mechanical and thermal measurements; design of experimental tests and set-up for space systems; design of measurement systems based on vision systems and laser scanners; robotics; autonomous vehicles; uncertainty evaluation

E-Mail Website
Guest Editor
1. Department of Industrial Engineering, Università Degli Studi di Padova, Via Venezia 1, 35131 Padova, Italy
2. Center for Studies and Activities for Space, Via Venezia 15, 35131 Padova, Italy
Interests: design, realization, and qualification of instruments and mechanisms for space applications; machine-vision-based localization methods for rovers; pose estimation; simultaneous localization and mapping (SLAM); active vision
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
German Aerospace Center (DLR), Institute of Robotics and Mechatronics, Cologne, Germany
Interests: multi-robot SLAM; multimodal place recognition; learning-based localization and mapping approaches; multi-robot and mission coordination for long-term robotic autonomy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Contributions to this Special Issue are welcomed in the field of attitude and position measurement systems, in particular vision-based and LiDAR-based, for two main applications: the proximity navigation of spacecraft and the autonomous navigation of vehicles in unstructured environments.

The importance of relative navigation between satellites and spacecraft is continuously growing since the number of possible applications is increasing, for instance, the flight formation of a set of small satellites, rendezvous and docking for satellite maintenance or for end-of-life operations and space debris mitigation.

A growing interest for rover navigation in unstructured environments and, in particular, for in situ operations for planetary exploration is being demonstrated by several planned mobile robotic missions in the upcoming years, such as ESA Mars2020, NASA Mars2020, ROSCOSMOS Luna-25 and DLR/JAXA Mars Moons eXploration.

The main topics of this Special Issue are:

  • Vision-based and LiDAR-based navigation and mapping for planetary robots;
  • Vision-based and LiDAR-based relative navigation for flight formation or between a chaser and a target spacecraft (collaborative or non-collaborative; active or passive; known or unknown; provided with markers or markerless);
  • Novel sensor setups and approaches for perception, navigation and interaction with an unstructured and GNSS-denied environment;
  • Relative navigation techniques for rendezvous and docking maneuvers between spacecraft;
  • Global and/or local map building in unstructured environments;
  • Novel technologies for mapping, navigation and terrain analysis;
  • Advances in the calibration procedures and techniques of mono- or multi-sensor systems for relative and absolute navigation;
  • Instrumentation and measurements for the navigation of UAV in planetary environments;
  • Sensor fusion techniques for aerospace applications;
  • Metrological evaluation and characterization of Machine Learning approaches for the navigation of autonomous spacecraft and vehicles in space applications and planetary exploration.

Dr. Marco Pertile
Dr. Sebastiano Chiodini
Dr. Riccardo Giubilato
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.

Published Papers (1 paper)

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

Research

29 pages, 8771 KiB  
Article
ALIEN: Assisted Learning Invasive Encroachment Neutralization for Secured Drone Transportation System
by Simeon Okechukwu Ajakwe, Vivian Ukamaka Ihekoronye, Dong-Seong Kim and Jae-Min Lee
Sensors 2023, 23(3), 1233; https://doi.org/10.3390/s23031233 - 20 Jan 2023
Cited by 5 | Viewed by 2149
Abstract
Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can [...] Read more.
Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can provide accurate risk assessment of autonomous aerial vehicles. Using deep neural networks and related technologies, this study proposes an artificial intelligence (AI) collaborative surveillance strategy for identifying, verifying, validating, and responding to malicious use of drones in a drone transportation network. The dataset for simulation consists of 3600 samples of 9 distinct conveyed objects and 7200 samples of the visioDECT dataset obtained from 6 different drone types flown under 3 different climatic circumstances (evening, cloudy, and sunny) at different locations, altitudes, and distance. The ALIEN model clearly demonstrates high rationality across all metrics, with an F1-score of 99.8%, efficiency with the lowest noise/error value of 0.037, throughput of 16.4 Gbps, latency of 0.021, and reliability of 99.9% better than other SOTA models, making it a suitable, proactive, and real-time avionic vehicular technology enabler for sustainable and secured DTS. Full article
Show Figures

Figure 1

Back to TopTop