Active Methods in Autonomous Navigation

A special issue of Robotics (ISSN 2218-6581).

Deadline for manuscript submissions: 31 May 2024 | Viewed by 5720

Special Issue Editors


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Guest Editor
Laboratory of Robotics and Automation, Democritus University of Thrace, Xanthi, Greece
Interests: autonomous robots; visual-based navigation; place recognition; loop closure detection; SLAM

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Guest Editor
Mechatronics & Systems Automation Lab, Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, Greece
Interests: robotic vision; localization and mapping; place recognition

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Guest Editor
Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
Interests: computer vision; robotics; quadrotors; deep learning; image processing

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Guest Editor
Robotics, Brain and Cognitive Sciences, Italian Institute of Technology, Genova, Italy
Interests: robotics; brain and cognitive sciences

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Guest Editor
Perception & Robotics Group, Computer Science, University of Maryland, College Park, MD, USA
Interests: robots with vision; manipulation; navigation

Special Issue Information

Dear Colleagues,

The goal of this Special Issue on “Active methods in autonomous navigation” is to bring together researchers, industry professionals, and enthusiasts across different sectors related to navigation, such as driverless car technology, unmanned aerial vehicles (UAVs), humanoid locomotion, rover navigation, social navigation, and SLAM—including re-localization and loop-closure detection, swarm navigation, and semantic mapping, coupling their functionality with perception and action recognition. Moreover, we also encourage size, weight, area, and power (SWAP)—aware navigation methods and bio-inspired approaches for mobile-robot autonomy. Our discussion will range from previously experienced problems to contemporary solutions and future trends, focusing on purposive perception planning since it remains an open problem in the community.

Call for Papers

We invite the submission of papers related to autonomous navigation based on active perception or action and perception-coupled methods. Topics of interest for this workshop and the associated Special Issue include (but are not limited to) papers describing active solutions in a series of areas:

  • Autonomous navigation;
  • Perception–action coupling;
  • Driverless cars;
  • Unmanned aerial vehicles (UAVs);
  • Size, weight, area and power (SWAP)-aware design;
  • Bio-inspired navigation;
  • Planetary exploration;
  • Swarm behavior;
  • Social navigation;
  • Semantic mapping and navigation;
  • Visual place recognition;
  • Simultaneous localization and mapping (SLAM);
  • Visual odometry;
  • Hyper-dimensional computing for perception;
  • Human action recognition;
  • Space robotics.

Dr. Konstantinos Tsintotas
Dr. Loukas Bampis
Dr. Nitin J Sanket
Prof. Dr. Antonios Gasteratos
Prof. Dr. Giulio Sandini
Prof. Dr. Yiannis Aloimonos
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. Robotics is an international peer-reviewed open access monthly 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 1800 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.

Published Papers (3 papers)

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22 pages, 1188 KiB  
Article
Online Odometry Calibration for Differential Drive Mobile Robots in Low Traction Conditions with Slippage
by Carlo De Giorgi, Daniela De Palma and Gianfranco Parlangeli
Robotics 2024, 13(1), 7; https://doi.org/10.3390/robotics13010007 - 27 Dec 2023
Viewed by 1582
Abstract
This paper addresses a systematic method for odometry calibration of a differential-drive mobile robot moving on arbitrary paths in the presence of slippage and an algorithm encoding it which is well fit for online applications. It exploits the redundancy of sensors commonly available [...] Read more.
This paper addresses a systematic method for odometry calibration of a differential-drive mobile robot moving on arbitrary paths in the presence of slippage and an algorithm encoding it which is well fit for online applications. It exploits the redundancy of sensors commonly available on ground mobile robots, such as encoders, gyroscopes, and IMU, to promptly detect slippage phenomena during the calibration process and effectively address their impact on odometry. The proposed technique has been validated through exhaustive numerical simulations and compared with other available odometry calibration methods. The simulation results confirm that the proposed methodology mitigates the impact of poor calibration, conducted without considering possible slipping phenomena, on reaching a target position, reducing the error by up to a maximum of 35 times. This restores the robot’s performance to a calibration condition close to that of a slip-free scenario, confirming the effectiveness of the approach and its robustness against slippage phenomena. Full article
(This article belongs to the Special Issue Active Methods in Autonomous Navigation)
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33 pages, 82129 KiB  
Article
Implicit Shape Model Trees: Recognition of 3-D Indoor Scenes and Prediction of Object Poses for Mobile Robots
by Pascal Meißner and Rüdiger Dillmann
Robotics 2023, 12(6), 158; https://doi.org/10.3390/robotics12060158 - 23 Nov 2023
Viewed by 1498
Abstract
This article describes an approach for mobile robots to identify scenes in configurations of objects spread across dense environments. This identification is enabled by intertwining the robotic object search and the scene recognition on already detected objects. We proposed “Implicit Shape Model (ISM) [...] Read more.
This article describes an approach for mobile robots to identify scenes in configurations of objects spread across dense environments. This identification is enabled by intertwining the robotic object search and the scene recognition on already detected objects. We proposed “Implicit Shape Model (ISM) trees” as a scene model to solve these two tasks together. This article presents novel algorithms for ISM trees to recognize scenes and predict object poses. For us, scenes are sets of objects, some of which are interrelated by 3D spatial relations. Yet, many false positives may occur when using single ISMs to recognize scenes. We developed ISM trees, which is a hierarchical model of multiple interconnected ISMs, to remedy this. In this article, we contribute a recognition algorithm that allows the use of these trees for recognizing scenes. ISM trees should be generated from human demonstrations of object configurations. Since a suitable algorithm was unavailable, we created an algorithm for generating ISM trees. In previous work, we integrated the object search and scene recognition into an active vision approach that we called “Active Scene Recognition”. An efficient algorithm was unavailable to make their integration using predicted object poses effective. Physical experiments in this article show that the new algorithm we have contributed overcomes this problem. Full article
(This article belongs to the Special Issue Active Methods in Autonomous Navigation)
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28 pages, 66441 KiB  
Article
Real-Time 3D Map Building in a Mobile Robot System with Low-Bandwidth Communication
by Alfin Junaedy, Hiroyuki Masuta, Kei Sawai, Tatsuo Motoyoshi and Noboru Takagi
Robotics 2023, 12(6), 157; https://doi.org/10.3390/robotics12060157 - 22 Nov 2023
Cited by 2 | Viewed by 1551
Abstract
This paper presents a new 3D map building technique using a combination of 2D SLAM and 3D objects that can be implemented on relatively low-cost hardware in real-time. Recently, 3D visualization of the real world became increasingly important. In robotics, it is not [...] Read more.
This paper presents a new 3D map building technique using a combination of 2D SLAM and 3D objects that can be implemented on relatively low-cost hardware in real-time. Recently, 3D visualization of the real world became increasingly important. In robotics, it is not only required for intelligent control, but also necessary for operators to provide intuitive visualization. SLAM is generally applied for this purpose, as it is considered a basic ability for truly autonomous robots. However, due to the increase in the amount of data, real-time processing is becoming a challenge. Therefore, in order to address this problem, we combine 2D data and 3D objects to create a new 3D map. The combination is simple yet robust based on rotation, translation, and clustering techniques. The proposed method was applied to a mobile robot system for indoor observation. The results show that real-time performance can be achieved by the system. Furthermore, we also combine high and low-bandwidth networks to deal with network problems that usually occur in wireless communication. Thus, robust wireless communication can be established, as it ensures that the missions can be continued even if the system loses the main network. Full article
(This article belongs to the Special Issue Active Methods in Autonomous Navigation)
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