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Sensors for Path Planning and Navigation in Robotics and Autonomous Vehicles

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 5516

Special Issue Editors

Prof. Dr. Alexander Ferrein

E-Mail Website
Guest Editor
MASCOR Institute, FH Aachen University of Applied Sciences, Eupener Str. 70, 52066 Aachen, Germany
Interests: AI; robotics; autonomous systems; high-level control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Michael Reke

E-Mail Website
Guest Editor
MASCOR Institute, FH Aachen University of Applied Sciences, Hohenstaufenallee 10, 52064 Aachen, Germany
Interests: autonomous driving; automotive electronics and software
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For successful mission deployment, robots and autonomous vehicles need robust and safe navigation and path planning algorithms that can cope with unforeseen obstacles and changing environment conditions. While a rich body of work on navigation and path planning methods exists, with this Special Issue we want to turn our attention towards the sensors that those systems operating in real-world environments need to be equipped with to provide the required robust and safe navigation and path planning capabilities. On the sensor hand, many new developments in solid-state LiDAR sensors, 4D radars and high-speed cameras, among others, have recently been observed. Concerning data processing there are discussions about early fusion approaches to combine sensors at the raw data level (e.g., for object detection). Additionally, multiple sensors are arranged around robots and vehicles to realize 360° perception, but also to guarantee stable localization under all conditions. Furthermore, the ideal sensor combination and data evaluation technology to ensure functional safety is still under discussion.
How do these topics advance the field of navigating autonomous systems?

We solicit contributions addressing topics including but not limited to:

  • Novel sensor technologies;
  • Examples of real-world applications with focus on the used sensor technologies;
  • Novel navigation/path planning approaches;
  • Novel data evaluation and sensor fusion algorithms and technologies;
  • Examples of applied sensor and data processing architectures for object detection, localization and safety purposes.

Prof. Dr. Alexander Ferrein
Prof. Dr. Michael Reke
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

  • sensors technology
  • autonomous vehicles
  • intelligent systems
  • sensor/data processing
  • sensor fusion
  • path planning
  • navigation

Published Papers (5 papers)

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Research

36 pages, 34495 KiB  
Article
A Novel 3D Reconstruction Sensor Using a Diving Lamp and a Camera for Underwater Cave Exploration
by Quentin Massone, Sébastien Druon and Jean Triboulet
Sensors 2024, 24(12), 4024; https://doi.org/10.3390/s24124024 - 20 Jun 2024
Viewed by 286
Abstract
Aquifer karstic structures, due to their complex nature, present significant challenges in accurately mapping their intricate features. Traditional methods often rely on invasive techniques or sophisticated equipment, limiting accessibility and feasibility. In this paper, a new approach is proposed for a non-invasive, low-cost [...] Read more.
Aquifer karstic structures, due to their complex nature, present significant challenges in accurately mapping their intricate features. Traditional methods often rely on invasive techniques or sophisticated equipment, limiting accessibility and feasibility. In this paper, a new approach is proposed for a non-invasive, low-cost 3D reconstruction using a camera that observes the light projection of a simple diving lamp. The method capitalizes on the principles of structured light, leveraging the projection of light contours onto the karstic surfaces. By capturing the resultant light patterns with a camera, three-dimensional representations of the structures are reconstructed. The simplicity and portability of the equipment required make this method highly versatile, enabling deployment in diverse underwater environments. This approach is validated through extensive field experiments conducted in various aquifer karstic settings. The results demonstrate the efficacy of this method in accurately delineating intricate karstic features with remarkable detail and resolution. Furthermore, the non-destructive nature of this technique minimizes disturbance to delicate aquatic ecosystems while providing valuable insights into the subterranean landscape. This innovative methodology not only offers a cost-effective and non-invasive means of mapping aquifer karstic structures but also opens avenues for comprehensive environmental monitoring and resource management. Its potential applications span hydrogeological studies, environmental conservation efforts, and sustainable water resource management practices in karstic terrains worldwide. Full article
(This article belongs to the Special Issue Sensors for Path Planning and Navigation in Robotics and Autonomous Vehicles)
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17 pages, 4788 KiB  
Article
Intelligent Path Planning with an Improved Sparrow Search Algorithm for Workshop UAV Inspection
by Jinwei Zhang, Xijing Zhu and Jing Li
Sensors 2024, 24(4), 1104; https://doi.org/10.3390/s24041104 - 8 Feb 2024
Viewed by 869
Abstract
Intelligent workshop UAV inspection path planning is a typical indoor UAV path planning technology. The UAV can conduct intelligent inspection on each work area of the workshop to solve or provide timely feedback on problems in the work area. The sparrow search algorithm [...] Read more.
Intelligent workshop UAV inspection path planning is a typical indoor UAV path planning technology. The UAV can conduct intelligent inspection on each work area of the workshop to solve or provide timely feedback on problems in the work area. The sparrow search algorithm (SSA), as a novel swarm intelligence optimization algorithm, has been proven to have good optimization performance. However, the reduction in the SSA’s search capability in the middle or late stage of iterations reduces population diversity, leading to shortcomings of the algorithm, including low convergence speed, low solution accuracy and an increased risk of falling into local optima. To overcome these difficulties, an improved sparrow search algorithm (namely the chaotic mapping–firefly sparrow search algorithm (CFSSA)) is proposed by integrating chaotic cube mapping initialization, firefly algorithm disturbance search and tent chaos mapping perturbation search. First, chaotic cube mapping was used to initialize the population to improve the distribution quality and diversity of the population. Then, after the sparrow search, the firefly algorithm disturbance and tent chaos mapping perturbation were employed to update the positions of all individuals in the population to enable a full search of the algorithm in the solution space. This technique can effectively avoid falling into local optima and improve the convergence speed and solution accuracy. The simulation results showed that, compared with the traditional intelligent bionic algorithms, the optimized algorithm provided a greatly improved convergence capability. The feasibility of the proposed algorithm was validated with a final simulation test. Compared with other SSA optimization algorithms, the results show that the CFSSA has the best efficiency. In an inspection path planning problem, the CFSSA has its advantages and applicability and is an applicable algorithm compared to SSA optimization algorithms. Full article
(This article belongs to the Special Issue Sensors for Path Planning and Navigation in Robotics and Autonomous Vehicles)
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28 pages, 12227 KiB  
Article
Research on Trajectory-Tracking Control System of Tracked Wall-Climbing Robots
by Haoyan Zhang, Jiaqi Wu, Yang An, Pengshu Xie and Da Cui
Sensors 2024, 24(1), 144; https://doi.org/10.3390/s24010144 - 27 Dec 2023
Cited by 1 | Viewed by 877
Abstract
Different from the vehicles and robots that move on the ground, complex and nonlinear track–wall interactions bring considerable difficulties to the accurate control of tracked wall-climbing robots due to the effect of gravity and adsorption. In this article, the authors propose a trajectory-tracking [...] Read more.
Different from the vehicles and robots that move on the ground, complex and nonlinear track–wall interactions bring considerable difficulties to the accurate control of tracked wall-climbing robots due to the effect of gravity and adsorption. In this article, the authors propose a trajectory-tracking control system for tracked wall-climbing robots based on the fuzzy logic computed-torque control (FLCT) method. A key element in the proposed control strategy is to consider the adsorption force and gravity compensation based on the dynamic model. Validated via numerical simulations and experiments, the results show that the proposed controller can track the reference trajectory quickly, accurately and stably. Full article
(This article belongs to the Special Issue Sensors for Path Planning and Navigation in Robotics and Autonomous Vehicles)
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44 pages, 16432 KiB  
Article
Viewpoint Planning for Range Sensors Using Feature Cluster Constrained Spaces for Robot Vision Systems
by Alejandro Magaña, Michiel Vlaeyen, Han Haitjema, Philipp Bauer, Benedikt Schmucker and Gunther Reinhart
Sensors 2023, 23(18), 7964; https://doi.org/10.3390/s23187964 - 18 Sep 2023
Cited by 1 | Viewed by 1009
Abstract
The efficient computation of viewpoints for solving vision tasks comprising multi-features (regions of interest) represents a common challenge that any robot vision system (RVS) using range sensors faces. The characterization of valid and robust viewpoints is even more complex within real applications that [...] Read more.
The efficient computation of viewpoints for solving vision tasks comprising multi-features (regions of interest) represents a common challenge that any robot vision system (RVS) using range sensors faces. The characterization of valid and robust viewpoints is even more complex within real applications that require the consideration of various system constraints and model uncertainties. Hence, to address some of the challenges, our previous work outlined the computation of valid viewpoints as a geometrical problem and proposed feature-based constrained spaces (C-spaces) to tackle this problem efficiently for acquiring one feature. The present paper extends the concept of C-spaces to consider multi-feature problems using feature cluster constrained spaces (GC-spaces). A GC-space represents a closed-form, geometrical solution that provides an infinite set of valid viewpoints for acquiring a cluster of features satisfying diverse viewpoint constraints. Furthermore, the current study outlines a generic viewpoint planning strategy based on GC-spaces for solving vision tasks comprising multi-feature scenarios effectively and efficiently. The applicability of the proposed framework is validated on two different industrial vision systems used for dimensional metrology tasks. Full article
(This article belongs to the Special Issue Sensors for Path Planning and Navigation in Robotics and Autonomous Vehicles)
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14 pages, 3134 KiB  
Article
Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy
by Yuhan Li, Ruizhi Ruan, Zupeng Zhou, Anqing Sun and Xiaonan Luo
Sensors 2023, 23(9), 4398; https://doi.org/10.3390/s23094398 - 29 Apr 2023
Cited by 6 | Viewed by 1805
Abstract
This paper presents a novel method for the dynamic positioning of an unmanned underwater vehicle (UUV) with unknown trajectories based on an autonomous tracking buoy (PUVV-ATB) that indirectly positions the UUV using ultra-short baseline measurements. The method employs a spatial location geometric model [...] Read more.
This paper presents a novel method for the dynamic positioning of an unmanned underwater vehicle (UUV) with unknown trajectories based on an autonomous tracking buoy (PUVV-ATB) that indirectly positions the UUV using ultra-short baseline measurements. The method employs a spatial location geometric model and divides the positioning process into four steps, including data preprocessing to detect geometric errors and apply mean filtering, direction capture, position tracking, and position synchronization. To achieve these steps, a new adaptive tracking control algorithm is proposed that does not require trajectory prediction and is applied to the last three steps. The algorithm is deployed to the buoy for tracking simulation and sea trial experiments, and the results are compared with those of a model predictive control algorithm. The autonomous tracking buoy based on the adaptive tracking control algorithm runs more stably and can better complete the precise tracking task for the UUV with a positioning error of less than 10 cm. This method breaks the premise of trajectory prediction based on traditional tracking control algorithms, providing a new direction for further research on UUV localization. Furthermore, the conclusion of this paper has important reference value for other research and application fields related to UUV. Full article
(This article belongs to the Special Issue Sensors for Path Planning and Navigation in Robotics and Autonomous Vehicles)
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