Women in Robotics

A special issue of Robotics (ISSN 2218-6581).

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 10918

Special Issue Editors


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Guest Editor
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Room 223, 1206 West Green Street, Urbana, IL 61801, USA
Interests: control and optimization; autonomous systems; machine learning; neural networks, game theory, and their applications in aerospace, robotics, mechanical, agricultural, electrical, petroleum, biomedical engineering, and elderly care
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Guest Editor
Department of Psychology, Director of the Laboratory of Behavioural Cognitive Systems (BeCogSys), Università degli Studi della Campania “Luigi Vanvitelli”, International Institute for Advanced Scientific Studies (IIASS), 81100 Caserta, Italy
Interests: social robotics; assistive robotics’ technology; robotics’ social acceptance

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Guest Editor
Professor of Computer Science, Chair of Computational Intelligence, Faculty of Computer Science Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106 Magdeburg, Germany
Interests: computational intelligence; multi-objective optimization and decision-making; swarm intelligence; swarm robotics

Special Issue Information

Dear Colleagues,

To celebrate the achievements of women in the robotics research area, this Special Issue, entitled "Women in Robotics ", will feature women and men co-authors, comprising leading experts in robotics, along with colleagues and junior researchers. We will also greatly appreciate the contributions of any other experts (no gender limitation) on topics broadly involving robots and robotics, to be included in this Special Issue being put together to celebrate women in the field. We hope that this Special Issue will further encourage and promote the scientific contributions of women who are researchers in this field. Papers in all areas of robotics, including but not limited to social robotics, robot acceptance, developmental robotics, robotics design, optimization, control, learning, and experimentation, among many others, are welcome.

Prof. Dr. Naira Hovakimyan
Prof. Dr. Anna Esposito
Prof. Dr. Sanaz Mostaghim
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. Robotics is an international peer-reviewed open access monthly 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 1800 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

  • robotics
  • control
  • learning
  • design
  • optimization
  • experimentation
  • social robotic
  • robots’ acceptance
  • developmental robotics
  • assistive technologies
  • human-robot interaction
  • human-in-the-loop
  • adaptation
  • beliefs and mental state attribution vision
  • perception
  • joint and social attention
  • eye tracking and gaze estimation
  • learning algorithms
  • sensors and sensors’ limits
  • fusions and processing of multimodal signals
  • swarm robotics

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Published Papers (2 papers)

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Research

15 pages, 2141 KiB  
Article
Singularity Avoidance for Cart-Mounted Hand-Guided Collaborative Robots: A Variational Approach
by Erica Salvato, Walter Vanzella, Gianfranco Fenu and Felice Andrea Pellegrino
Robotics 2022, 11(4), 79; https://doi.org/10.3390/robotics11040079 - 6 Aug 2022
Cited by 4 | Viewed by 2579
Abstract
Most collaborative robots (cobots) can be taught by hand guiding: essentially, by manually jogging the robot, an operator teaches some configurations to be employed as via points. Based on those via points, Cartesian end-effector trajectories such as straight lines, circular arcs or splines [...] Read more.
Most collaborative robots (cobots) can be taught by hand guiding: essentially, by manually jogging the robot, an operator teaches some configurations to be employed as via points. Based on those via points, Cartesian end-effector trajectories such as straight lines, circular arcs or splines are then constructed. Such methods can, in principle, be employed for cart-mounted cobots (i.e., when the jogging involves one or two linear axes, besides the cobot axes). However, in some applications, the sole imposition of via points in Cartesian space is not sufficient. On the contrary, albeit the overall system is redundant, (i) the via points must be reached at the taught joint configurations, and (ii) the undesirable singularity (and near-singularity) conditions must be avoided. The naive approach, consisting of setting the cart trajectory beforehand (for instance, by imposing a linear-in-time motion law that crosses the taught cart configurations), satisfies the first need, but does not guarantee the satisfaction of the second. Here, we propose an approach consisting of (i) a novel strategy for decoupling the planning of the cart trajectory and that of the robot joints, and (ii) a novel variational technique for computing the former in a singularity-aware fashion, ensuring the avoidance of a class of workspace singularity and near-singularity configurations. Full article
(This article belongs to the Special Issue Women in Robotics)
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23 pages, 3503 KiB  
Article
Time Coordination and Collision Avoidance Using Leader-Follower Strategies in Multi-Vehicle Missions
by Camilla Tabasso, Venanzio Cichella, Syed Bilal Mehdi, Thiago Marinho and Naira Hovakimyan
Robotics 2021, 10(1), 34; https://doi.org/10.3390/robotics10010034 - 13 Feb 2021
Cited by 15 | Viewed by 5473
Abstract
In recent years, the increasing popularity of multi-vehicle missions has been accompanied by a growing interest in the development of control strategies to ensure safety in these scenarios. In this work, we propose a control framework for coordination and collision avoidance in cooperative [...] Read more.
In recent years, the increasing popularity of multi-vehicle missions has been accompanied by a growing interest in the development of control strategies to ensure safety in these scenarios. In this work, we propose a control framework for coordination and collision avoidance in cooperative multi-vehicle missions based on a speed adjustment approach. The overall problem is decoupled in a coordination problem, in order to ensure coordination and inter-vehicle safety among the agents, and a collision-avoidance problem to guarantee the avoidance of non-cooperative moving obstacles. We model the network over which the cooperative vehicles communicate using tools from graph theory, and take communication losses and time delays into account. Finally, through a rigorous Lyapunov analysis, we provide performance bounds and demonstrate the efficacy of the algorithms with numerical and experimental results. Full article
(This article belongs to the Special Issue Women in Robotics)
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