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Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition

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

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 6816

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Special Issue Editors

Dr. Gregor Klančar

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Guest Editor

Laboratory of Control Systems and Cybernetics, Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
Interests: autonomous mobile robots; motion control; trajectory tracking; path planning; localization; multiagent systems
Special Issues, Collections and Topics in MDPI journals

Dr. Marija Seder

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Guest Editor

Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Interests: autonomous mobile robots; motion planning; motion control; path planning; coverage planning; environment exploration
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Sašo Blažič

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Guest Editor

Laboratory of Control Systems and Cybernetics, Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia
Interests: control of nonlinear systems; modeling of nonlinear systems; autonomous mobile systems; mobile robotics; motion control; trajectory tracking
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on mobile robotics systems, where we are witnessing a widespread surge in current applications as well as promising future applications that are made possible due to recent technologies in sensors development. Mobile robots are already started to penetrate our homes, modern manufacturing and warehouse systems are hard to imagine without automated guided vehicles, self-driving cars already drive in normal traffic, flying taxies are about to take off and offer new travel experience, drones already have applications in delivery and remote sensing, not to mention applications in agriculture, construction, medical care, surveillance, entertainment, and others where some will also appear in unforeseen ways, all of them offering an emerging market with great potential. Advanced sensor technologies are of crucial importance in mobile robotics—a multidisciplinary research field—for obtaining automated or autonomous operation of mobile robots in these applications. They have a part in every navigation, motion control, action planning, decision making, environment sensing, localization, awareness, object detection, target tracking, or object manipulation.

This Special Issue on advanced sensor technologies welcomes contributions on recent developments in mobile robotics systems and associated research from a theoretic and application perspective. Topics related to mobile robotics include but are not limited to new sensor developments, innovations in theory, algorithms, reviews, sensor applications, sensor processing, sensor fusion, sensor calibration, object tracking, localization, scene recognition, SLAM, control algorithms, navigation, motion control, mobile robotics, and autonomous system design.

Dr. Gregor Klančar
Dr. Marija Seder
Prof. Dr. Sašo Blažič
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

mobile robots localization
SLAM mapping and navigation sensor-based planning motion control sensor
fusion learning and evolving algorithms in robots collaborative robots multi-robot systems

Published Papers (7 papers)

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Research

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31 pages, 13428 KiB

Open AccessArticle

SEG-SLAM: Dynamic Indoor RGB-D Visual SLAM Integrating Geometric and YOLOv5-Based Semantic Information

by Peichao Cong, Jiaxing Li, Junjie Liu, Yixuan Xiao and Xin Zhang

Sensors 2024, 24(7), 2102; https://doi.org/10.3390/s24072102 - 25 Mar 2024

Viewed by 571

Abstract

Simultaneous localisation and mapping (SLAM) is crucial in mobile robotics. Most visual SLAM systems assume that the environment is static. However, in real life, there are many dynamic objects, which affect the accuracy and robustness of these systems. To improve the performance of visual SLAM systems, this study proposes a dynamic visual SLAM (SEG-SLAM) system based on the orientated FAST and rotated BRIEF (ORB)-SLAM3 framework and you only look once (YOLO)v5 deep-learning method. First, based on the ORB-SLAM3 framework, the YOLOv5 deep-learning method is used to construct a fusion module for target detection and semantic segmentation. This module can effectively identify and extract prior information for obviously and potentially dynamic objects. Second, differentiated dynamic feature point rejection strategies are developed for different dynamic objects using the prior information, depth information, and epipolar geometry method. Thus, the localisation and mapping accuracy of the SEG-SLAM system is improved. Finally, the rejection results are fused with the depth information, and a static dense 3D mapping without dynamic objects is constructed using the Point Cloud Library. The SEG-SLAM system is evaluated using public TUM datasets and real-world scenarios. The proposed method is more accurate and robust than current dynamic visual SLAM algorithms. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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26 pages, 9725 KiB

Open AccessArticle

Phased Array Ultrasonic Method for Robotic Preload Measurement in Offshore Wind Turbine Bolted Connections

by Yashar Javadi, Brandon Mills, Charles MacLeod, David Lines, Farhad Abad, Saeid Lotfian, Ali Mehmanparast, Gareth Pierce, Feargal Brennan, Anthony Gachagan and Carmelo Mineo

Sensors 2024, 24(5), 1421; https://doi.org/10.3390/s24051421 - 22 Feb 2024

Viewed by 942

Abstract

This paper presents a novel approach for preload measurement of bolted connections, specifically tailored for offshore wind applications. The proposed method combines robotics, Phased Array Ultrasonic Testing (PAUT), nonlinear acoustoelasticity, and Finite Element Analysis (FEA). Acceptable defects, below a pre-defined size, are shown to have an impact on preload measurement, and therefore conducting simultaneous defect detection and preload measurement is discussed in this paper. The study demonstrates that even slight changes in the orientation of the ultrasonic transducer, the non-automated approach, can introduce a significant error of up to 140 MPa in bolt stress measurement and therefore a robotic approach is employed to achieve consistent and accurate measurements. Additionally, the study emphasises the significance of considering average preload for comparison with ultrasonic data, which is achieved through FEA simulations. The advantages of the proposed robotic PAUT method over single-element approaches are discussed, including the incorporation of nonlinearity, simultaneous defect detection and stress measurement, hardware and software adaptability, and notably, a substantial improvement in measurement accuracy. Based on the findings, the paper strongly recommends the adoption of the robotic PAUT approach for preload measurement, whilst acknowledging the required investment in hardware, software, and skilled personnel. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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11 pages, 1794 KiB

Open AccessArticle

Measurements of Electrodermal Activity, Tissue Oxygen Saturation, and Visual Analog Scale for Different Cuff Pressures

by Youngho Kim, Incheol Han, Jeyong Jung, Sumin Yang, Seunghee Lee, Bummo Koo, Soonjae Ahn, Yejin Nam and Sung-Hyuk Song

Sensors 2024, 24(3), 917; https://doi.org/10.3390/s24030917 - 31 Jan 2024

Viewed by 666

Abstract

The quantification of comfort in binding parts, essential human–machine interfaces (HMI) for the functioning of rehabilitation robots, is necessary to reduce physical strain on the user despite great achievements in their structure and control. This study aims to investigate the physiological impacts of binding parts by measuring electrodermal activity (EDA) and tissue oxygen saturation (StO₂). In Experiment 1, EDA was measured from 13 healthy subjects under three different pressure conditions (10, 20, and 30 kPa) for 1 min using a pneumatic cuff on the right thigh. In Experiment 2, EDA and StO₂ were measured from 10 healthy subjects for 5 min. To analyze the correlation between EDA parameters and the decrease in StO₂, a survey using the visual analog scale (VAS) was conducted to assess the level of discomfort at each pressure. The EDA signal was decomposed into phasic and tonic components, and the EDA parameters were extracted from these two components. RM ANOVA and a post hoc paired t-test were used to determine significant differences in parameters as the pressure increased. The results showed that EDA parameters and the decrease in StO₂ significantly increased with the pressure increase. Among the extracted parameters, the decrease in StO₂ and the mean SCL proved to be effective indicators. Such analysis outcomes would be highly beneficial for studies focusing on the comfort assessment of the binding parts of rehabilitation robots. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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14 pages, 2668 KiB

Open AccessArticle

Space Robot Sensor Noise Amelioration Using Trajectory Shaping

by Emily Kuck and Timothy Sands

Sensors 2024, 24(2), 666; https://doi.org/10.3390/s24020666 - 20 Jan 2024

Viewed by 593

Abstract

Robots in space are necessarily extremely light and lack structural stiffness resulting in natural frequencies of resonance so low as to reside inside the attitude controller’s bandwidth. A variety of input trajectories can be used to drive a controller’s attempt to ameliorate the control-structural interactions where feedback is provided by low-quality, noisy sensors. Traditionally, step functions are used as the ideal input trajectory. However, step functions are not ideal in many applications, as they are discontinuous. Alternative input trajectories are explored in this manuscript and applied to an example system that includes a flexible appendage attached to a rigid main body. The main body is controlled by a reaction wheel. The equations of motion of the flexible appendage, rigid body, and reaction wheel are derived. A benchmark feedback controller is developed to account for the rigid body modes. Additional filters are added to compensate for the system’s flexible modes. Sinusoidal trajectories are autonomously generated to feed the controller. Benchmark feedforward whiplash compensation is additionally implemented for comparison. The method without random errors with the smallest error is the sinusoidal trajectory method, which showed a 97.39% improvement when compared to the baseline response when step trajectories were commanded, while the sinusoidal method was inferior to traditional step trajectories when sensor noise and random errors were present. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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19 pages, 7575 KiB

Open AccessArticle

Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care

by Jan Vanus, Radim Hercik and Petr Bilik

Sensors 2023, 23(21), 8953; https://doi.org/10.3390/s23218953 - 03 Nov 2023

Viewed by 842

Abstract

It is important for older and disabled people who live alone to be able to cope with the daily challenges of living at home. In order to support independent living, the Smart Home Care (SHC) concept offers the possibility of providing comfortable control of operational and technical functions using a mobile robot for operating and assisting activities to support independent living for elderly and disabled people. This article presents a unique proposal for the implementation of interoperability between a mobile robot and KNX technology in a home environment within SHC automation to determine the presence of people and occupancy of occupied spaces in SHC using measured operational and technical variables (to determine the quality of the indoor environment), such as temperature, relative humidity, light intensity, and CO₂ concentration, and to locate occupancy in SHC spaces using magnetic contacts monitoring the opening/closing of windows and doors by indirectly monitoring occupancy without the use of cameras. In this article, a novel method using nonlinear autoregressive Neural Networks (NN) with exogenous inputs and nonlinear autoregressive is used to predict the CO₂ concentration waveform to transmit the information from KNX technology to mobile robots for monitoring and determining the occupancy of people in SHC with better than 98% accuracy. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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31 pages, 9102 KiB

Open AccessArticle

Smooth Autonomous Patrolling for a Differential-Drive Mobile Robot in Dynamic Environments

by Ana Šelek, Marija Seder and Ivan Petrović

Sensors 2023, 23(17), 7421; https://doi.org/10.3390/s23177421 - 25 Aug 2023

Cited by 1 | Viewed by 1096

Abstract

Today, mobile robots have a wide range of real-world applications where they can replace or assist humans in many tasks, such as search and rescue, surveillance, patrolling, inspection, environmental monitoring, etc. These tasks usually require a robot to navigate through a dynamic environment with smooth, efficient, and safe motion. In this paper, we propose an online smooth-motion-planning method that generates a smooth, collision-free patrolling trajectory based on clothoid curves. Moreover, the proposed method combines global and local planning methods, which are suitable for changing large environments and enabling efficient path replanning with an arbitrary robot orientation. We propose a method for planning a smoothed path based on the golden ratio wherein a robot’s orientation is aligned with a new path that avoids unknown obstacles. The simulation results show that the proposed algorithm reduces the patrolling execution time, path length, and deviation of the tracked trajectory from the patrolling route compared to the original patrolling method without smoothing. Furthermore, the proposed algorithm is suitable for real-time operation due to its computational simplicity, and its performance was validated through the results of an experiment employing a differential-drive mobile robot. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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Review

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15 pages, 496 KiB

Open AccessReview

Anomaly Detection Methods in Autonomous Robotic Missions

by Shivoh Chirayil Nandakumar, Daniel Mitchell, Mustafa Suphi Erden, David Flynn and Theodore Lim

Sensors 2024, 24(4), 1330; https://doi.org/10.3390/s24041330 - 19 Feb 2024

Viewed by 1147

Abstract

Since 2015, there has been an increase in articles on anomaly detection in robotic systems, reflecting its growing importance in improving the robustness and reliability of the increasingly utilized autonomous robots. This review paper investigates the literature on the detection of anomalies in Autonomous Robotic Missions (ARMs). It reveals different perspectives on anomaly and juxtaposition to fault detection. To reach a consensus, we infer a unified understanding of anomalies that encapsulate their various characteristics observed in ARMs and propose a classification of anomalies in terms of spatial, temporal, and spatiotemporal elements based on their fundamental features. Further, the paper discusses the implications of the proposed unified understanding and classification in ARMs and provides future directions. We envisage a study surrounding the specific use of the term anomaly, and methods for their detection could contribute to and accelerate the research and development of a universal anomaly detection system for ARMs. Full article

(This article belongs to the Special Issue Advanced Sensors Technologies Applied in Mobile Robotics: 2nd Edition)

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