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Autonomous Navigation in Robotics: A New Challenge towards Social Robots

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 8425

Special Issue Editors


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Guest Editor
Laboratory of Robotics and Artificial Vision, Department of Computer and Communication Technology, University of Extremadura, 10003 Cáceres, Spain
Interests: social robotics; robot navigation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Aston University, UK
Interests: social robotics; human–robot interaction; deep learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
University of León, Spain
Interests: social robotics; cognitive robotics; human–robot interaction

Special Issue Information

Dear Colleagues,

The future generation of robots needs a set of skills to carry out complex tasks autonomously. Among them, autonomous navigation is one of the fundamental capabilities with which these robots must be equipped. Robot navigation in real environments is not simple and has been the focus of the scientific community’s effort for decades. Robot navigation requires, among other functions, environmental perception, path-planning, moving between targets, and real-time reactions to unexpected events.

If people are also included in these real environments, the solutions are increasingly complex. Navigation is no longer limited to reaching the destination by optimizing, for example, the travel time or distance traveled; it must also take into account social conventions, such as not invading personal spaces or not interrupting a conversation. Social navigation is a new challenge for the scientific community and involves using different technologies and strategies: sensing, localization, mapping, approaching, people and object tracking, human–robot interaction, learning, etc.

This Special Issue aims to contribute to the state-of-the-art and present current application of robot navigation, with particular attention to social robots.

Dr. Pedro Núñez Trujillo
Dr. Luis Manso Fernández-Argüéllez
Dr. Luis Vicente Calderita
Guest Editors

Manuscript Submission Information

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Keywords

  • Perception and localization.
  • SLAM
  • Path-planning approaches for navigation in environment with people
  • Data fusion for mobile robot navigation
  • Sensor networks for mobile robot navigation
  • Human–robot interaction for social navigation
  • People and robot tracking for navigation
  • Adaptive robot navigation and control
  • Tracking algorithms
 
 

Published Papers (3 papers)

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Research

26 pages, 5496 KiB  
Article
Waymarking in Social Robots: Environment Signaling Using Human–Robot Interaction
by Ana Corrales-Paredes, María Malfaz, Verónica Egido-García and Miguel A. Salichs
Sensors 2021, 21(23), 8145; https://doi.org/10.3390/s21238145 - 06 Dec 2021
Cited by 3 | Viewed by 2128
Abstract
Travellers use the term waymarking to define the action of posting signs, or waymarks, along a route. These marks are intended to be points of reference during navigation for the environment. In this research, we will define waymarking as the skill of a [...] Read more.
Travellers use the term waymarking to define the action of posting signs, or waymarks, along a route. These marks are intended to be points of reference during navigation for the environment. In this research, we will define waymarking as the skill of a robot to signal the environment or generate information to facilitate localization and navigation, both for its own use and for other robots as well. We present an automated environment signaling system using human–robot interaction and radio frequency identification (RFID) technology. The goal is for the robot, through human–robot interaction, to obtain information from the environment and use this information to carry out the signaling or waymarking process. HRI will play a key role in the signaling process since this type of communication makes it possible to exchange more specific and enriching information. The robot uses common phrases such as “Where am I?” and “Where can I go?”, just as we humans do when we ask other people for information about the environment. It is also possible to guide the robot and “show” it the environment to carry out the task of writing the signs. The robot will use the information received to create, update, or improve the navigation data in the RFID signals. In this paper, the signaling process will be described, how the robot acquires the information for signals, writing and updating process and finally, the implementation and integration in a real social robot in a real indoor environment. Full article
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15 pages, 6801 KiB  
Article
Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework
by Nicolas Montés, Francisco Chinesta, Marta C. Mora, Antonio Falcó, Lucia Hilario, Nuria Rosillo and Enrique Nadal
Sensors 2021, 21(12), 3943; https://doi.org/10.3390/s21123943 - 08 Jun 2021
Cited by 2 | Viewed by 2864
Abstract
This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property of the proposed technique is that the computational cost is [...] Read more.
This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property of the proposed technique is that the computational cost is negligible in real-time, even if the robot is disturbed or the goal is changed. The main idea of the method is the off-line generation, for a given environment, of the whole set of paths from any start and goal configurations of a mobile robot, namely the computational vademecum, derived from a harmonic potential field in order to use it on-line for decision-making purposes. Up until now, the resolution of the Laplace or Poisson equations has been based on traditional numerical techniques unfeasible for real-time calculation. This drawback has prevented the extensive use of harmonic functions in autonomous navigation, despite their powerful properties. The numerical technique that reverses this situation is the Proper Generalized Decomposition. To demonstrate and validate the properties of the PGD-vademecum in a potential-guided path planning framework, both real and simulated implementations have been developed. Simulated scenarios, such as an L-Shaped corridor and a benchmark bug trap, are used, and a real navigation of a LEGO®MINDSTORMS robot running in static environments with variable start and goal configurations is shown. This device has been selected due to its computational and memory-restricted capabilities, and it is a good example of how its properties could help the development of social robots. Full article
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17 pages, 3058 KiB  
Article
Multiple-Joint Pedestrian Tracking Using Periodic Models
by Marzieh Dolatabadi, Jos Elfring and René van de Molengraft
Sensors 2020, 20(23), 6917; https://doi.org/10.3390/s20236917 - 03 Dec 2020
Cited by 4 | Viewed by 1742
Abstract
Estimating accurate positions of multiple pedestrians is a critical task in robotics and autonomous cars. We propose a tracker based on typical human motion patterns to track multiple pedestrians. This paper assumes that the legs’ reflection and extension angles are approximately changing periodically [...] Read more.
Estimating accurate positions of multiple pedestrians is a critical task in robotics and autonomous cars. We propose a tracker based on typical human motion patterns to track multiple pedestrians. This paper assumes that the legs’ reflection and extension angles are approximately changing periodically during human motion. A Fourier series is fitted in order to describe the moving, such as describing the position and velocity of the hip, knee, and ankle. Our tracker receives the position of the ankle, knee, and hip as measurements. As a proof of concept, we compare our tracker with state-of-the-art methods. The proposed models have been validated by experimental data, the Human Gait Database (HuGaDB), and the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) tracking benchmark. The results indicate that our tracker is able to estimate the reflection and extension angles with a precision of 90.97%. Moreover, the comparison shows that the tracking precision increases up to 1.3% with the proposed tracker when compared to a constant velocity based tracker. Full article
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