Autonomous and Intelligent Robotics

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 2710

Special Issue Editor


E-Mail Website
Guest Editor
Department of Design Engineering and Robotics, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
Interests: smart factory; robot programming and intelligent robotics; engineering and management of innovation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue, entitled "Autonomous and Intelligent Robotics", welcomes contributions exploring the state of the art of autonomous systems, intelligent industrial robotics, and their transformative implications. This Special Issue covers a broad array of topics, extending from the design and implementation of autonomous and intelligent robotic systems to the intricate societal and ethical challenges they introduce.

The relevance of this field is profound as advanced robotic systems are becoming fundamental components in a wide variety of sectors. They are reshaping the operational landscape of manufacturing, healthcare, agriculture, and space exploration by enhancing efficiency, safety, and precision. Their transformative influence is underlined by the emergence of novel applications across a range of domains. This includes autonomous vehicles revolutionizing transportation, sophisticated healthcare technologies facilitating precision medicine, smart agricultural robots enhancing crop yield and sustainability, and advanced manufacturing robots streamlining production processes. Furthermore, in the realm of space exploration, autonomous and intelligent robots are playing a crucial role, enabling deep-space missions and intricate tasks beyond human reach. Within service industries, these robots are increasingly being deployed for tasks such as logistics, hospitality, and customer service, fundamentally redefining these sectors. This broad spectrum of applications serves to highlight the expansive and transformative impact of autonomous and intelligent robotics on our world. This shift is primarily powered by the integration of artificial intelligence and machine learning, which has significantly amplified the capabilities of these robots. Yet, along with these promising innovations, they also bring about complex challenges related to job displacement, privacy, and ethical dilemmas. This Special Issue aims to highlight these multifaceted aspects, offering an all-encompassing perspective on the present state and future trajectory of autonomous and intelligent robotics. It calls for contributions from a wide range of areas, including, but not limited to, human–robot interaction, multi-robot systems, robotic process automation, and intelligent industrial robotics. This Special Issue seeks to maintain a balanced focus between the technological evolution and the broader societal implications, highlighting the field's timely significance and necessity.

Potential topics for the Special Issue:

  1. Design and implementation of autonomous robotic systems;
  2. Application of AI and machine learning in autonomous robotics;
  3. Intelligent industrial robotics in manufacturing;
  4. Ethical and societal implications of autonomous and intelligent robotics;
  5. Impact of autonomous robotics on the healthcare sector;
  6. Advancements in intelligent agricultural robots;
  7. The future of transportation: Autonomous vehicles;
  8. Robotic process automation (RPA) in service industries;
  9. Robotics in deep-space exploration;
  10. Human–robot interaction in everyday life;
  11. Development and challenges of multi-robot systems;
  12. Intelligent robots in logistics and supply chain;
  13. Privacy concerns in the era of autonomous robotics;
  14. The impact of intelligent robotics on job markets;
  15. Case studies on the integration of autonomous systems in traditional industries;
  16. Development of laws and regulations for intelligent robotics;
  17. The use of swarm intelligence in robotics;
  18. Sensor technology in autonomous and intelligent robots;
  19. Designing user interfaces for human–robot interaction;
  20. Security challenges and solutions in autonomous and intelligent robotics;
  21. Collaborative robots (Cobots) in the industrial setting;
  22. Autonomous robotics in disaster response and recovery;
  23. Energy efficiency and sustainability in autonomous and intelligent robotics;
  24. Data analytics in the evolution of intelligent robotics;
  25. Autonomous and intelligent robotics in educational settings;
  26. Computer vision in enhancing the capabilities of autonomous and intelligent robotics;
  27. Advances in tactile sensing and haptic feedback for autonomous robots;
  28. Application of intelligent robotics in non-traditional domains like arts, entertainment, and sports;
  29. Development and integration of emotion recognition capabilities in robots for improved human–robot interaction;
  30. The influence of 5G and future network technologies on the performance and capabilities of autonomous and intelligent robots.

Prof. Dr. Stelian Brad
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

  • autonomous robotics
  • intelligent industrial robotics
  • artificial intelligence
  • machine learning
  • human–robot interaction
  • multi-robot systems
  • robotic process automation
  • societal implications
  • ethical considerations
  • advanced robot applications

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)

Order results
Result details
Select all
Export citation of selected articles as:

Research

32 pages, 6863 KiB  
Article
Dynamic Affect-Based Motion Planning of a Humanoid Robot for Human-Robot Collaborative Assembly in Manufacturing
by S. M. Mizanoor Rahman
Electronics 2024, 13(6), 1044; https://doi.org/10.3390/electronics13061044 - 11 Mar 2024
Cited by 1 | Viewed by 1338
Abstract
The objective was to investigate the impacts of the robot’s dynamic affective expressions in task-related scenarios on human–robot collaboration (HRC) and performance in human–robot collaborative assembly tasks in flexible manufacturing. A human–robot hybrid cell was developed to facilitate a human co-worker and a [...] Read more.
The objective was to investigate the impacts of the robot’s dynamic affective expressions in task-related scenarios on human–robot collaboration (HRC) and performance in human–robot collaborative assembly tasks in flexible manufacturing. A human–robot hybrid cell was developed to facilitate a human co-worker and a robot to collaborate to assemble a few parts into a final product. The collaborative robot was a humanoid manufacturing robot with the ability to display its affective states due to changes in task scenarios on its face. The assembly task was divided into several subtasks, and based on an optimization strategy, the subtasks were optimally allocated to the human and the robot. A computational model of the robot’s affective states was derived inspired by that of humans following the biomimetic approach, and an affect-based motion planning strategy for the robot was proposed to enable the robot to adjust its motions and behaviors with task situations and communicate (inform) the situations to the human co-worker through affective expressions. The HRC and the assembly performance for the affect-based motion planning were experimentally evaluated based on a comprehensive evaluation scheme and were compared with two alternative conditions: (i) motion planning that did not display affective states, and (ii) motion planning that displayed text messages instead of displaying affective states to communicate the situations to the human co-worker. The results clearly showed that the dynamic affect-based motion planning produced significantly better HRC and assembly performance than that produced by motion planning associated with the display of no affective states or text messages. The results encouraged employing manufacturing robots with dynamic affective expressions to collaborate with humans in flexible assembly in manufacturing to improve HRC and assembly performance. Full article
(This article belongs to the Special Issue Autonomous and Intelligent Robotics)
Show Figures

Figure 1

18 pages, 4606 KiB  
Article
A Novel Online Path Planning Algorithm for Multi-Robots Based on the Secondary Immune Response in Dynamic Environments
by Yafeng Jiang, Liang Zhang, Mingxin Yuan and Yi Shen
Electronics 2024, 13(3), 562; https://doi.org/10.3390/electronics13030562 - 30 Jan 2024
Viewed by 849
Abstract
To solve the online path planning of multi-robots in dynamic environments, a novel secondary immune responses-based immune path planning algorithm (SIRIPPA) is presented. The algorithm comprises two immune stages. In the primary immune stage, the antibodies are mainly designed for obstacle avoidance and [...] Read more.
To solve the online path planning of multi-robots in dynamic environments, a novel secondary immune responses-based immune path planning algorithm (SIRIPPA) is presented. The algorithm comprises two immune stages. In the primary immune stage, the antibodies are mainly designed for obstacle avoidance and a primary immune kinetic model is designed in terms of the different impacts of obstacles on robot behaviors. The primary immune antibodies and their concentration values are mainly taken as the prior knowledge to accelerate the secondary immune response. In the secondary immune stage, aiming at the same obstacle antigens, which invade once more, the immune system quickly produces many behavior antibodies. Combining the primary immune results and secondary immune response results, the path planning performance of multi-robots is improved. The simulation experiment indicates that, in static environment tests, compared to corresponding immune planning algorithms, the SIRIPPA exhibits an average reduction of 6.22% in the global path length, a decrease of 23.00% in the average smoothness, and an average energy consumption reduction of 27.55%; the algorithm exhibits a better performance for path planning. The simulation test in a dynamic environment shows the good flexibility and stability of the SIRIPPA. Additionally, the experimental results in a real environment further support the validity of the SIRIPPA. Full article
(This article belongs to the Special Issue Autonomous and Intelligent Robotics)
Show Figures

Figure 1

Back to TopTop