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Special Issue "Assistance Robotics and Sensors"

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

Deadline for manuscript submissions: 20 March 2021.

Special Issue Editors

Prof. Dr. Santiago T. Puente
Website
Guest Editor
Automatics, Robotics and Computer Vision Group, Computer Science Research Institute, University of Alicante, Alicante 03690, Spain
Interests: dexterous grasping; outdoor manipulation; neuro-robotics; myoelectric control; marine robotics; deep learning; production automation and automatic disassembly
Special Issues and Collections in MDPI journals
Prof. Dr. Fernando Torres
Website
Guest Editor
Automatics, Robotics and Computer Vision Group, Computer Science Research Institute, University of Alicante, Alicante 03690, Spain
Interests: intelligent robotic manipulation; visual control of robots; robot perception systems; field robots and advanced automation for industry 4.0; artificial vision engineering and e-learning
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, exploitation of assistance robotics has experienced a significant growth, mostly based on the development of sensor and processing technologies with the increasing interest in improving interaction of robots with humans in a more natural way. Robots are required to assist humans in the industry, in the manufacturing workspace, in the rehabilitation process, as well as in the medical environment. Robots are used to achieve ambient assisted living and to help older adults. Furthermore, assistive robots are used in security, search, or rescue operations, and to interact with humans with infectious diseases.

This Special Issue is focused on breakthrough developments in the field of assistive robotics, including current scientific progress in machine learning, deep learning, reinforcement learning, and imitation learning to enable assistive robots to help humans in any environment, as well as any supportive sensorial system that facilitates interaction between humans and robots at home or in the industrial environment. In addition to the aforementioned environments, methods and algorithms that combine sensors to enable assistive robots can be considered. Papers should address innovative solutions in these fields. Both review articles and original research papers are solicited.

Prof. Dr. Santiago T. Puente
Prof. Dr. Fernando Torres
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 papers will be 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 2000 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

  • Assistive robotics to human operators in industry and in manufacturing workspaces
  • Assistive robotics in the rehabilitation process and the medical environment
  • Robots to achieve ambient assisted living
  • Assistive robots in operations of security, search, or rescue
  • Robotics to interact with humans with infectious diseases
  • Machine learning, deep learning, reinforcement learning, and imitation learning to enable assistive robots to humans in any environment
  • Methods and algorithms that combine sensors to enable assistive robots
  • Any supportive sensorial system that facilitates interaction between humans and robots

Published Papers (1 paper)

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Research

Open AccessArticle
Impact of Acoustic and Interactive Disruptive Factors during Robot-Assisted Surgery—A Virtual Surgical Training Model
Sensors 2020, 20(20), 5891; https://doi.org/10.3390/s20205891 - 17 Oct 2020
Abstract
The use of virtual reality trainers for teaching minimally invasive surgical techniques has been established for a long time in conventional laparoscopy as well as robotic surgery. The aim of the present study was to evaluate the impact of reproducible disruptive factors on [...] Read more.
The use of virtual reality trainers for teaching minimally invasive surgical techniques has been established for a long time in conventional laparoscopy as well as robotic surgery. The aim of the present study was to evaluate the impact of reproducible disruptive factors on the surgeon’s work. In a cross-sectional investigation, surgeons were tested with regard to the impact of different disruptive factors when doing exercises on a robotic-surgery simulator (Mimic Flex VRTM). Additionally, we collected data about the participants’ professional experience, gender, age, expertise in playing an instrument, and expertise in playing video games. The data were collected during DRUS 2019 (Symposium of the German Society for Robot-assisted Urology). Forty-two surgeons attending DRUS 2019 were asked to participate in a virtual robotic stress training unit. The surgeons worked in various specialties (visceral surgery, gynecology, and urology) and had different levels of expertise. The time taken to complete the exercise (TTCE), the final score (FSC), and blood loss (BL) were measured. In the basic exercise with an interactive disruption, TTCE was significantly longer (p < 0.01) and FSC significantly lower (p < 0.05). No significant difference in TTCE, FSC, or BL was noted in the advanced exercise with acoustic disruption. Performance during disruption was not dependent on the level of surgical experience, gender, age, expertise in playing an instrument, or playing video games. A positive correlation was registered between self-estimation and surgical experience. Interactive disruptions have a greater impact on the performance of a surgeon than acoustic ones. Disruption affects the performance of experienced as well as inexperienced surgeons. Disruption in daily surgery should be evaluated and minimized in the interest of the patient’s safety. Full article
(This article belongs to the Special Issue Assistance Robotics and Sensors)
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