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Electronics
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Intelligent Control of Mobile Robotics
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Intelligent Control of Mobile Robotics

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

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 13207

Special Issue Editors

Dr. Angel García-Olaya

E-Mail Website
Guest Editor
Computer Science Department, Universidad Carlos III de Madrid, 28911 Leganés, Madrid, Spain
Interests: artificial intelligence; automated task planning; robotics for space and underwater exploration; social assistive robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Andrea Orlandini

E-Mail Website
Guest Editor
Institute of Cognitive Science and Technology, National Research Council of Italy, 00185 Roma, Italy
Interests: artificial intelligence; automated planning and scheduling; model-based control; human–robot interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since the first experiments with Shakey at the Artificial Intelligence Center of Stanford Robotics Institute, the Artificial Intelligence and Robotics fields have been intimately connected. Several movies ranging from Fritz Lang’s Metropolis to Alex Garland’s Ex Machina have helped to cement this tie in the collective imagination. Indeed, the two are often seen as a single field: All robots are intelligent, and all intelligent devices are robots.

Such integration, however, has shown to be quite challenging, leading AI and Robotics to be developed as distinct research lines. Indeed, in real practice, and despite some early attempts to put them together, these two fields have worked in isolation for many years. Only recently has the combination of reliable and flexible robotic platforms and powerful AI techniques begun to lead to a new interest in integrating AI and Robotics, enabling intelligent mobile robots systems to get out of the lab and be used in commercial applications.

The aim of this Special Issue on “Intelligent Control of Mobile Robotics” is to provide an overview of this wide field. It should be of interest to the AI, Robotics, and Control communities. We welcome papers focusing on intelligent mobile robotics systems, architectures, and applications. Autonomous robotics systems, intelligent and reliable control techniques, vision and natural language processing algorithms for mobile robots or social and ethical research exploring relations between people and these new companions or co-workers fall within the scope of this Special Issue. Papers with experiments on real robots are preferred, but works in simulation are also welcome. Both theoretical and practical papers are welcome.

Dr. Angel García-Olaya
Dr. Andrea Orlandini
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. 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

  • AI in mobile robotics
  • Deliberation in mobile robotics
  • Machine learning for mobile robotics
  • Intelligent control approaches for mobile robotics
  • Mixed-initiative planning and adjustable autonomy
  • Autonomous robot systems
  • Path and trajectory planning
  • Mobile multi-robot systems and human-robot teaming
  • Formal methods for robot planning and control
  • Social mobile robotics
  • Behavior transparency and explainability
  • Real-world robotic applications

Published Papers (4 papers)

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Research

14 pages, 2518 KiB  
Article
The 3D Position Estimation and Tracking of a Surface Vehicle Using a Mono-Camera and Machine Learning
by Ju Wang, Wookjin Choi, Jose Diaz and Curtrell Trott
Electronics 2022, 11(14), 2141; https://doi.org/10.3390/electronics11142141 - 8 Jul 2022
Cited by 1 | Viewed by 2485
Abstract
The ability to obtain the 3D position of target vehicles is essential to managing and coordinating a multi-robot operation. We investigate an ML-backed object localization and tracking system to estimate the target’s 3D position based on a mono-camera input. The passive vision-only technique [...] Read more.
The ability to obtain the 3D position of target vehicles is essential to managing and coordinating a multi-robot operation. We investigate an ML-backed object localization and tracking system to estimate the target’s 3D position based on a mono-camera input. The passive vision-only technique provides a robust field awareness in challenging conditions such as GPS-denied or radio-silent environments. Our processing pipeline utilizes a YOLOv5 neural network as the back-end detection module and a temporal filtering technique to improve detection and tracking accuracy. The filtering process effectively removes false positive labels to improve tracking accuracy. We propose a piecewise projection model to predict the target 3D position from the estimated 2D bounding box. Our projection model utilizes the co-plane property of ground vehicles to calculate 2D–3D mapping. Experimental results show that the piecewise model is more accurate than existing methods when the training dataset is not evenly distributed in the sampling space. Our piecewise model outperforms the singular RANSAC-based and the 6DPose methods by 28% in location errors. A less than 10-m error is observed for most near-to-mid-range cases. Full article
(This article belongs to the Special Issue Intelligent Control of Mobile Robotics)
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17 pages, 426 KiB  
Article
A Coloured Petri Net- and D* Lite-Based Traffic Controller for Automated Guided Vehicles
by Imanol Mugarza and Juan Carlos Mugarza
Electronics 2021, 10(18), 2235; https://doi.org/10.3390/electronics10182235 - 12 Sep 2021
Cited by 8 | Viewed by 2854
Abstract
Mobile robots, such as Automated Guided Vehicles (AGVs), are increasingly employed in automated manufacturing systems or automated warehouses. They are used for many kinds of applications, such as goods and material handling. These robots may also share industrial areas and routes with humans. [...] Read more.
Mobile robots, such as Automated Guided Vehicles (AGVs), are increasingly employed in automated manufacturing systems or automated warehouses. They are used for many kinds of applications, such as goods and material handling. These robots may also share industrial areas and routes with humans. Other industrial equipment (i.e., forklifts) could also obstruct the outlined routes. With this in mind, in this article, a coloured Petri net-based traffic controller is proposed for collision-free AGV navigation, in which other elements moving throughout the industrial area, such as humans, are also taken into account for the trajectory planning and obstacle avoidance. For the optimal path and collision-free trajectory planning and traffic control, the D* Lite algorithm was used. Moreover, a case study and an experimental validation of the suggested solution in an industrial shop floor are presented. Full article
(This article belongs to the Special Issue Intelligent Control of Mobile Robotics)
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44 pages, 10261 KiB  
Article
Agent in a Box: A Framework for Autonomous Mobile Robots with Beliefs, Desires, and Intentions
by Patrick Gavigan and Babak Esfandiari
Electronics 2021, 10(17), 2136; https://doi.org/10.3390/electronics10172136 - 2 Sep 2021
Cited by 1 | Viewed by 2803
Abstract
This paper provides the Agent in a Box for developing autonomous mobile robots using Belief-Desire-Intention (BDI) agents. This framework provides the means of connecting the agent reasoning system to the environment, using the Robot Operating System (ROS), in a way that is flexible [...] Read more.
This paper provides the Agent in a Box for developing autonomous mobile robots using Belief-Desire-Intention (BDI) agents. This framework provides the means of connecting the agent reasoning system to the environment, using the Robot Operating System (ROS), in a way that is flexible to a variety of application domains which use different sensors and actuators. It also provides the needed customisation to the agent’s reasoner for ensuring that the agent’s behaviours are properly prioritised. Behaviours which are common to all mobile robots, such as for navigation and resource management, are provided. This allows developers for specific application domains to focus on domain-specific code. Agents implemented using this approach are rational, mission capable, safety conscious, fuel autonomous, and understandable. This method was used for demonstrating the capability of BDI agents to control robots for a variety of application domains. These included simple grid environments, a simulated autonomous car, and a prototype mail delivery robot. From these case studies, the approach was demonstrated as capable of controlling the robots in the application domains. It also reduced the development burden needed for applying the approach to a specific robot. Full article
(This article belongs to the Special Issue Intelligent Control of Mobile Robotics)
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29 pages, 16022 KiB  
Article
Project ARES: Driverless Transportation System. Challenges and Approaches in an Unstructured Road
by Pablo Marin-Plaza, David Yagüe, Francisco Royo, Miguel Ángel de Miguel, Francisco Miguel Moreno, Alejandro Ruiz-de-la-Cuadra, Fernando Viadero-Monasterio, Javier Garcia, José Luis San Roman and José María Armingol
Electronics 2021, 10(15), 1753; https://doi.org/10.3390/electronics10151753 - 21 Jul 2021
Cited by 11 | Viewed by 3229
Abstract
The expansion of electric vehicles in urban areas has paved the way toward the era of autonomous vehicles, improving the performance in smart cities and upgrading related driving problems. This field of research opens immediate applications in the tourism areas, airports or business [...] Read more.
The expansion of electric vehicles in urban areas has paved the way toward the era of autonomous vehicles, improving the performance in smart cities and upgrading related driving problems. This field of research opens immediate applications in the tourism areas, airports or business centres by greatly improving transport efficiency and reducing repetitive human tasks. This project shows the problems derived from autonomous driving such as vehicle localization, low coverage of 4G/5G and GPS, detection of the road and navigable zones including intersections, detection of static and dynamic obstacles, longitudinal and lateral control and cybersecurity aspects. The approaches proposed in this article are sufficient to solve the operational design of the problems related to autonomous vehicle application in the special locations such as rough environment, high slopes and unstructured terrain without traffic rules. Full article
(This article belongs to the Special Issue Intelligent Control of Mobile Robotics)
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