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Journals
Designs
Special Issues
Advancements in Robotic Design, Manufacturing, and the Action-Perception Loop
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Advancements in Robotic Design, Manufacturing, and the Action-Perception Loop

A special issue of Designs (ISSN 2411-9660).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 679

Special Issue Editors

Dr. Roveda Loris

E-Mail Website
Guest Editor
Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Scuola Universitaria Professionale della Svizzera Italiana (SUPSI), Università della Svizzera Italiana (USI) IDSIA-SUPSI, Manno, Switzerland
Interests: industrial robots; collaborative robots; control theory; wearable robotics; interaction control; human-robot collaboration; AI; ML
Special Issues, Collections and Topics in MDPI journals
Dr. Roberto Meattini

E-Mail Website
Guest Editor
Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, Bologna, Italy
Interests: robotic manipulation; human-robot interaction; assistive robotics; programming by demonstration; machine learning

Special Issue Information

Dear Colleagues,

Recent advancements in robotics research have underscored the importance of exploiting the link between robot perception and action, which, if considered as interconnected entities of a loop instead of separate processes, could enhance the geometric interpretation of perceptual information, the estimation of object models, the integration of grasp planning with machine learning, and long-horizon manipulation task sequences in industrial settings. Investigating the crucial relations between robot perception and action may contribute to overcoming current limitations and enable a new era of industrial automation to be unlocked.

This Special Issue aims to connect scientists who are actively working at the intersection of robotic manipulation and perception. Contributions to this Special Issue should present recent advancements and perspectives concerning robotic manipulation and perception for a diverse range of topics, including, but not limited to, deformable object manipulation, grasp stability, dexterous manipulation, active and interactive perception, robot learning, computer vision, tactile sensing, and learning from demonstration.

Dr. Roveda Loris
Dr. Roberto Meattini
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. Designs 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 1600 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
  • robotic manipulation
  • robotic perception
  • automation
  • machine learning
  • human–robot collaboration
  • deformable objects

Published Papers (1 paper)

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Research

30 pages, 3617 KiB  
Article
Energy Requirement Modeling for Automated Guided Vehicles Considering Material Flow and Layout Data
by Marvin Sperling and Kai Furmans
Designs 2024, 8(3), 48; https://doi.org/10.3390/designs8030048 - 21 May 2024
Viewed by 504
Abstract
Saving energy and resources has become increasingly important for industrial applications. Foremost, this requires knowledge about the energy requirement. For this purpose, this paper presents a state-based energy requirement model for mobile robots, e.g., automated guided vehicles or autonomous mobile robots, that determines [...] Read more.
Saving energy and resources has become increasingly important for industrial applications. Foremost, this requires knowledge about the energy requirement. For this purpose, this paper presents a state-based energy requirement model for mobile robots, e.g., automated guided vehicles or autonomous mobile robots, that determines the energy requirement by integrating the linearized power requirement parameters within each system state of the vehicle. The model and their respective system states were verified using a qualitative process analysis of 25 mobile robots from different manufacturers and validated by comparing simulated data with experimental data. For this purpose, power consumption measurements over 461 operating hours were performed in experiments with two different industrial mobile robots. System components of a mobile robot, which require energy, were classified and their power consumptions were measured individually. The parameters in the study consist of vehicle speed, load-handling duration, load, utilization, material flow and layout data, and charging infrastructure system frequency, yet these varied throughout the experiments. Validation of the model through real experiments shows that, in a 99% confidence interval, the relative deviation in the modeled power requirement for a small-scale vehicle is [−1.86%,−1.14%], whereas, for a mid-scale vehicle, it is [−0.73%,−0.31%]. This sets a benchmark for modeling the energy requirement of mobile robots with multiple influencing factors, allowing for an accurate estimation of the energy requirement of mobile robots. Full article
(This article belongs to the Special Issue Advancements in Robotic Design, Manufacturing, and the Action-Perception Loop)
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