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Latest Advances on Sensors and Perception for Climbing and Walking...
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Latest Advances on Sensors and Perception for Climbing and Walking Robots

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

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1182

Special Issue Editors

Prof. Dr. Manuel F. Silva

E-Mail Website
Guest Editor
Department of Electrical Engineering, Institute of Engineering of the Polytechnic Institute of Porto, 4249-015 Porto, Portugal
Interests: modelling; simulation; robotics; biological inspired robots; control and education in robotics and control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mohammad Osman Tokhi

E-Mail Website
Guest Editor
School of Engineering, London South Bank University, London SE1 0AA, UK
Interests: active noise and vibration control; adaptive/intelligent control; soft-computing modeling and control of dynamic systems; assistive robotics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Leonardo Mejia Rincon

E-Mail Website
Guest Editor
Automation, Control and Computation Engineer Department, Federal University of Santa Catarina, Florianópolis, Brazil
Interests: industrial robotics; robots for special applications; force capability optimization
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ebrahim Samer El Youssef

E-Mail Website
Guest Editor
Department of Automation and Control Engineering, and Computation, Federal University of Santa Catarina, Florianópolis, Brazil
Interests: robotics; unmanned aerial robots; wheeled mobile robots; nonlinear systems modelling and controlling

Special Issue Information

Dear Colleagues,

Climbing and walking robots are witnessing a very rapid development, with new systems and applications being introduced day-by-day. The innovations with them are occurring in very distinct areas, but there is a clear need for these systems to sense their surroundings to be able to adjust their behaviour to the perceived environment. Therefore, it is relevant for the latest developments to be shared among scientists and professors on the related topics, all around the world, to further enhance the advancement of the area.

Given this context, the objective of this Special Issue is to promote and disseminate the most recent research and development on sensors and perception for climbing and walking robots. The present issue will mainly gather enhanced and extended versions of papers selected out of those presented at the 26th issue of the International Conference Series on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR’2023). Authors who did not attend the conference are also welcomed to submit their research to this SI.

This SI will cover analysis (modelling and simulation) techniques, design approaches, and practical applications and realisations of sensing systems for robotic systems. A non-exhaustive list of topics is as follows:

  • Sensor networks;
  • Smart/intelligent sensors;
  • Sensor devices;
  • Sensor technology and applications in agriculture, services, industry, and the environment;
  • Optoelectronic and photonic sensors;
  • Optomechanical sensors;
  • Micro- and nanosensors;
  • Internet of Things;
  • Signal processing and data fusion in sensor systems;
  • Sensor interface;
  • Human–computer interaction;
  • Image sensors;
  • Sensor-captured imaging;
  • Vision/camera-based sensors;
  • 3D sensing;
  • Wearable sensors, devices, and electronics;
  • Sensors and robotics;
  • Multi-sensor positioning and navigation.

Prof. Dr. Manuel F. Silva
Prof. Dr. Mohammad Osman Tokhi
Prof. Dr. Leonardo Mejia Rincon
Prof. Dr. Ebrahim Samer El Youssef
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

  • guidance and navigation
  • innovative sensors and sensor networks
  • inspection
  • modelling and simulation
  • nature-inspired systems and solutions
  • perception and situation awareness
  • positioning and localisation
  • reconnaissance
  • sensor fusion
  • service robots

Published Papers (2 papers)

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Research

19 pages, 4592 KiB  
Article
Mobile Robot + IoT: Project of Sustainable Technology for Sanitizing Broiler Poultry Litter
by Alan Kunz Cechinel, Carlos Eduardo Soares, Sergio Genilson Pfleger, Leonardo Luiz Gambalonga Alves De Oliveira, Ederson Américo de Andrade, Claudia Damo Bertoli, Carlos Roberto De Rolt, Edson Roberto De Pieri, Patricia Della Méa Plentz and Juha Röning
Sensors 2024, 24(10), 3049; https://doi.org/10.3390/s24103049 - 11 May 2024
Viewed by 238
Abstract
The traditional aviary decontamination process involves farmers applying pesticides to the aviary’s ground. These agricultural defenses are easily dispersed in the air, making the farmers susceptible to chronic diseases related to recurrent exposure. Industry 5.0 raises new pillars of research and innovation in [...] Read more.
The traditional aviary decontamination process involves farmers applying pesticides to the aviary’s ground. These agricultural defenses are easily dispersed in the air, making the farmers susceptible to chronic diseases related to recurrent exposure. Industry 5.0 raises new pillars of research and innovation in transitioning to more sustainable, human-centric, and resilient companies. Based on these concepts, this paper presents a new aviary decontamination process that uses IoT and a robotic platform coupled with ozonizer (O3) and ultraviolet light (UVL). These clean technologies can successfully decontaminate poultry farms against pathogenic microorganisms, insects, and mites. Also, they can degrade toxic compounds used to control living organisms. This new decontamination process uses physicochemical information from the poultry litter through sensors installed in the environment, which allows accurate and safe disinfection. Different experimental tests were conducted to construct the system. First, tests related to measuring soil moisture, temperature, and pH were carried out, establishing the range of use and the confidence interval of the measurements. The robot’s navigation uses a back-and-forth motion that parallels the aviary’s longest side because it reduces the number of turns, reducing energy consumption. This task becomes more accessible because of the aviaries’ standardized geometry. Furthermore, the prototype was tested in a real aviary to confirm the innovation, safety, and effectiveness of the proposal. Tests have shown that the UV + ozone combination is sufficient to disinfect this environment. Full article
(This article belongs to the Special Issue Latest Advances on Sensors and Perception for Climbing and Walking Robots)
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11 pages, 6084 KiB  
Article
Exploring Human–Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion–Extension Performance across Varied Robot Assistance–Resistance Configurations
by Denis Mosconi, Yecid Moreno and Adriano Siqueira
Sensors 2024, 24(8), 2645; https://doi.org/10.3390/s24082645 - 21 Apr 2024
Viewed by 555
Abstract
Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to [...] Read more.
Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to improved patient outcomes and treatment efficiency. One of the points that must be taken into account when using robots in rehabilitation is their interaction with the patient, which must be safe for both and guarantee the effectiveness of the treatment. Therefore, the objective of this study was to assess the interaction between humans and an exoskeleton during the execution of knee flexion–extension movements under various configurations of robot assistance and resistance. The evaluation encompassed considerations of myoelectric activity, muscle recruitment, robot torque, and performed movement. To achieve this, an experimental protocol was implemented, involving an individual wearing the exoskeleton and executing knee flexion–extension motions while seated, with the robot configured in five distinct modes: passive (P), assistance on flexion (FA), assistance on extension (EA), assistance on flexion and extension (CA), and resistance on flexion and extension (CR). Results revealed distinctive patterns of movement and muscle recruitment for each mode, highlighting the complex interplay between human and robot; for example, the largest RMS tracking errors were for the EA mode (13.72 degrees) while the smallest for the CR mode (4.47 degrees), a non-obvious result; in addition, myoelectric activity was demonstrated to be greater for the completely assisted mode than without the robot (the maximum activation levels for the vastus medialis and vastus lateralis muscles were more than double those when the user had assistance from the robot). Tracking errors, muscle activations, and torque values varied across modes, emphasizing the need for careful consideration in configuring exoskeleton assistance and resistance to ensure effective and safe rehabilitation. Understanding these human–robot interactions is essential for developing precise rehabilitation programs, optimizing treatment effectiveness, and enhancing patient safety. Full article
(This article belongs to the Special Issue Latest Advances on Sensors and Perception for Climbing and Walking Robots)
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