Guidance, Navigation and Control of Mobile Robots

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1053

Special Issue Editors


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Guest Editor
School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
Interests: mobile robot navigation; teleoperation

E-Mail Website
Guest Editor
School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
Interests: visual navigation of UAV; image processing; target tracking and recognition
Special Issues, Collections and Topics in MDPI journals
Key Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
Interests: unmanned systems; information fusion; distributed control; navigation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mobile robots have become an increasingly important tool to modern society in the last decade. They have been widely deployed in numerous areas and applications, including the industrial, service, medical, socialization and defence sectors. Guidance, navigation and control are the core technologies that are used to enable the safe and reliable application of mobile robots in such areas. However, various environments and mobile robot configurations impose great challenges to their guidance, navigation and control system. Therefore, studies on the guidance, navigation and control of mobile robots to cope with different situations and applications have become a trend in recent years.

This Special Issue aims to assemble a collection of the state-of-the-art research achievements in the guidance, navigation and control of mobile robots, which deal with the primary challenges, such as self-localization in GNSS-denied areas, safe navigation through complex environments and the autonomous exploration and mapping of an unknown region.

Dr. Xiaolei Hou
Dr. Chunhui Zhao
Dr. Jinwen Hu
Guest Editors

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Keywords

  • mobile robots
  • state estimation
  • path and motion planning
  • motion control
  • autonomous exploration
  • multi-robot collaboration
  • SLAM

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Published Papers (1 paper)

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Research

28 pages, 34209 KiB  
Article
Autonomous Non-Communicative Navigation Assistance to the Ground Vehicle by an Aerial Vehicle
by Ashok Kumar Sivarathri and Amit Shukla
Machines 2025, 13(2), 152; https://doi.org/10.3390/machines13020152 - 17 Feb 2025
Viewed by 398
Abstract
Vision-based UAV-AGV (Unmanned Aerial Vehicle–Autonomous Ground Vehicle) systems are prominent for executing tasks in GPS (Global Positioning System)-inaccessible areas. One of the roles of the UAV is guiding the navigation of the AGV. Reactive/mapless navigation assistance to an AGV from a UAV is [...] Read more.
Vision-based UAV-AGV (Unmanned Aerial Vehicle–Autonomous Ground Vehicle) systems are prominent for executing tasks in GPS (Global Positioning System)-inaccessible areas. One of the roles of the UAV is guiding the navigation of the AGV. Reactive/mapless navigation assistance to an AGV from a UAV is well known and suitable for computationally less powerful systems. This method requires communication between both agents during navigation as per state of the art. However, communication delays and failures will cause failures in tasks, especially during outdoor missions. In the present work, we propose a mapless technique for the navigation of AGVs assisted by UAVs without communication of obstacles to AGVs. The considered scenario is that the AGV is undergoing sensor and communication module failure and is completely dependent on the UAV for its safe navigation. The goal of the UAV is to take AGV to the destination while guiding it to avoid obstacles. We exploit the autonomous tracking task between the UAV and AGV for obstacle avoidance. In particular, AGV tracking the motion of the UAV is exploited for the navigation of the AGV. YOLO (You Only Look Once) v8 has been implemented to detect the drone by AGV camera. The sliding mode control method is implemented for the tracking motion of the AGV and obstacle avoidance control. The job of the UAV is to localize obstacles in the image plane and guide the AGV without communicating with it. Experimental results are presented to validate the proposed method. This proves to be a significant technique for the safe navigation of the AGV when it is non-communicating and experiencing sudden sensor failure. Full article
(This article belongs to the Special Issue Guidance, Navigation and Control of Mobile Robots)
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