Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.6
Journals
Electronics
Special Issues
Multi-robot Systems: Collaboration, Control, and Path Planning
share announcement

Multi-robot Systems: Collaboration, Control, and Path Planning

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 2146

Special Issue Editor

Dr. Corrado Santoro

E-Mail Website
Guest Editor
Department of Mathematics and Informatics, University of Catania, Viale Andrea Doria, 6, 95125 Catania, CT, Italy
Interests: multi-agent system; distributed artificial intelligence; autonomous mobile robots; autonomous flying robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Multi-robot systems appear to be the next frontier of robotics: they comprise a set of autonomous robots living in a real-world environment that cooperate to achieve a common goal; therefore, during operation, each robot must not only take into account the problems related to its own control, but also, and above all, the fact that the overall goal is split into parts, each one in charge of a specific entity. This characteristic enables the pursuit of novel research related to interaction, cooperation and planning in the presence of a world populated by multiple artificial systems. Since “autonomy” is a contentious word, interaction must consider an exchange of meaningful messages that reflect the “state of mind” (knowledge, goals, plans, intentions, etc.) of each single robot, while cooperation and planning imply considering a state of mind that is spread among all the entities. In addition, the path followed by such robotic systems must consider the fact that robots, while exchanging data, may better optimize their movements by exploiting mutual knowledge. In other words, the technologies used to favor these aspects must deal with problems ranging from communication protocols to the meaningful semantics of the messages exchanged, state of mind representation, reasoning, path planning, goal achievement, etc.

The proposed Special Issue aims to gather novel research in the context described and considers, in particular, the following topics:

  • interaction protocols in multi-robot systems
  • distributed artificial intelligence
  • swarm intelligence
  • planning and reasoning in multi-robot systems
  • collaborative path planning
  • flock organization and formation
  • area coverage
  • application and case-studies of multi-robot systems

I look forward to receiving your contributions.

Dr. Corrado Santoro
Guest Editor

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. Electronics 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 2400 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

  • multi-robot
  • swarm robotics
  • intelligence
  • cooperative robot
  • deep learning

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 7251 KiB  
Article
Interactive Path Editing and Simulation System for Motion Planning and Control of a Collaborative Robot
by Taeho Yoo and Byoung Wook Choi
Electronics 2024, 13(14), 2857; https://doi.org/10.3390/electronics13142857 - 19 Jul 2024
Viewed by 639
Abstract
Robots in hazardous environments demand precise and advanced motion control, making extensive simulations crucial for verifying the safety of motion planning. This paper presents a simulation system that enables interactive path editing, allowing for motion planning in a simulated collaborative robot environment and [...] Read more.
Robots in hazardous environments demand precise and advanced motion control, making extensive simulations crucial for verifying the safety of motion planning. This paper presents a simulation system that enables interactive path editing, allowing for motion planning in a simulated collaborative robot environment and its real-world application. The system includes a simulation host, a control board, and a robot. Unity 3D on a Windows platform provides the simulation environment, while a virtual Linux environment runs ROS2 for execution. Unity sends edited motion paths to ROS2 using the Unity ROS TCP Connector package. The ROS2 MoveIt framework generates trajectories, which are synchronized back to Unity for simulation and real-world validation. To control the six-axis Indy7 collaborative robot, we used the MIO5272 embedded board as an EtherCAT master. Verified trajectories are sent to the target board, synchronizing the robot with the simulation in position and speed. Data are relayed from the host to the MIO5272 using ROS2 and the Data Distribution Service (DDS) to control the robot via EtherCAT communication. The system enables direct simulation and control of various trajectories for robots in hazardous environments. It represents a major advancement by providing safe and optimized trajectories through efficient motion planning and repeated simulations, offering a clear improvement over traditional time-consuming and error-prone teach pendant methods. Full article
(This article belongs to the Special Issue Multi-robot Systems: Collaboration, Control, and Path Planning)
►▼ Show Figures

Figure 1

15 pages, 2026 KiB  
Article
Machine Learning-Based Hand Pose Generation Using a Haptic Controller
by Jongin Choi, Jaehong Lee, Daniel Oh and Eung-Joo Lee
Electronics 2024, 13(10), 1970; https://doi.org/10.3390/electronics13101970 - 17 May 2024
Viewed by 1195
Abstract
In this study, we present a novel approach to derive hand poses from data input via a haptic controller, leveraging machine learning techniques. The input values received from the haptic controller correspond to the movement of five fingers, each assigned a value between [...] Read more.
In this study, we present a novel approach to derive hand poses from data input via a haptic controller, leveraging machine learning techniques. The input values received from the haptic controller correspond to the movement of five fingers, each assigned a value between 0.0 and 1.0 based on the applied pressure. The wide array of possible finger movements requires a substantial amount of motion capture data, making manual data integration difficult. This challenge is primary due to the need to process and incorporate large volumes of diverse movement information. To tackle this challenge, our proposed method automates the process by utilizing machine learning algorithms to convert haptic controller inputs into hand poses. This involves training a machine learning model using supervised learning, where hand poses are matched with their corresponding input values, and subsequently utilizing this trained model to generate hand poses in response to user input. In our experiments, we assessed the accuracy of the generated hand poses by analyzing the angles and positions of finger joints. As the quantity of training data increased, the margin of error decreased, resulting in generated poses that closely emulated real-world hand movements. Full article
(This article belongs to the Special Issue Multi-robot Systems: Collaboration, Control, and Path Planning)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop