Advances in Mobile Robots: Navigation, Motion Planning and Control

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

Deadline for manuscript submissions: 15 July 2024 | Viewed by 1341

Special Issue Editor


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Guest Editor
Department of Control and Computer Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Interests: posture control; bipedal robots; robots for posture rehabilitation
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Special Issue Information

Dear Colleagues,

Mobile robotics is a challenging and expanding area covering a large variety of domains, such as manufacturing, agriculture, military, health care and education.

Navigation and path planning are important aspects of autonomous or supervised (drones) mobile robots, but control is also considered. Biped robotics are the first to be considered, but multi-legged robots, carts with wheels for patient support and rim-less wheels as models for passive walking (i.e., inverted pendulum and foot placement estimation) are also valued.

The aim of this Special Issue is to bring together new advances in the navigation and control of mobile robotics. As these aspects have received separate attention in the past, the journal Electronics offers the opportunity to show the synergy between them.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Navigation: both autonomous and supervised navigation with fleet management, team coordination (e.g., robot soccer playing, Swarm intelligence, etc.) and remote navigation management (drones are also a kind of mobile robot).
  • Path planning: a priori or in dynamic online environment using on-board sensors, e.g., to direct to the robot on a specific path, avoiding obstacles, coping with irregular terrain, climbing and descending stairs.
  • Human–robot co-existence environments, especially in health care.
  • Control: control dynamics, balance, gait, especially human-like walking merging unstable (i.e., inverted pendulum) and stable (i.e., zero moment point) phases.

Prof. Dr. Giuseppe Menga
Guest Editor

Manuscript Submission Information

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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

  • mobile robotics
  • navigation
  • path planning
  • control of posture

Published Papers (1 paper)

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Research

20 pages, 10982 KiB  
Article
Research on Path Planning with the Integration of Adaptive A-Star Algorithm and Improved Dynamic Window Approach
by Tianjian Liao, Fan Chen, Yuting Wu, Huiquan Zeng, Sujian Ouyang and Jiansheng Guan
Electronics 2024, 13(2), 455; https://doi.org/10.3390/electronics13020455 - 22 Jan 2024
Viewed by 1134
Abstract
In response to the shortcomings of the traditional A-star algorithm, such as excessive node traversal, long search time, unsmooth path, close proximity to obstacles, and applicability only to static maps, a path planning method that integrates an adaptive A-star algorithm and an improved [...] Read more.
In response to the shortcomings of the traditional A-star algorithm, such as excessive node traversal, long search time, unsmooth path, close proximity to obstacles, and applicability only to static maps, a path planning method that integrates an adaptive A-star algorithm and an improved Dynamic Window Approach (DWA) is proposed. Firstly, an adaptive weight value is added to the heuristic function of the A-star algorithm, and the Douglas–Pucker thinning algorithm is introduced to eliminate redundant points. Secondly, a trajectory point estimation function is added to the evaluation function of the DWA algorithm, and the path is optimized for smoothness based on the B-spline curve method. Finally, the adaptive A-star algorithm and the improved DWA algorithm are integrated into the fusion algorithm of this article. The feasibility and effectiveness of the fusion algorithm are verified through obstacle avoidance experiments in both simulation and real environments. Full article
(This article belongs to the Special Issue Advances in Mobile Robots: Navigation, Motion Planning and Control)
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