Collection

Autonomous Navigation, Localization and Planning in Networked Unmanned Systems

Submission status
Closed

Unmanned systems have become an area of intense research within the robotics and control community, wherein Unmanned Ground/Aerial/Underwater Vehicles have covered a wide range of applications from the civil domain to the military domain, such as logistics, mine detection, building and environment monitoring, intruder detection and attacking, etc. In recent years, swarms or networks of such autonomous robots are emerging as a disruptive technology to enable highly reconfigurable, on-demand, distributed intelligent autonomous systems with high impact in many areas of science, technology, and society. In any application, networked and cooperative robots are expected to be more capable than a single large robot, offering significantly enhanced flexibility (adaptability, scalability, and maintainability) and robustness (reliability, survivability, and fault tolerance).

Autonomous navigation, localization, and planning are the three key supporting pillars for realizing the abovementioned intelligent and autonomous applications of unmanned systems. To date, the efforts in the study of these technologies have been continuously increasing, but many problems remain to be explored, discovered and solved. The primary purpose of this Article Collection is to showcase the latest achievements of theory and practice related to autonomous navigation, localization, and planning in the networked unmanned systems, aiming to inspire further research in the field.

The areas of interest include, but are not limited to:

-Survey of networked unmanned systems;

-Signal processing methods and sensor modules for autonomous unmanned systems;

-Autonomous navigation in GPS-denied environments;

-Multi-sensor target localization and tracking; Autonomous decision making for game and cooperation;

-Cooperative path planning and re-planning for homogeneous/non-homogeneous networks;

-Network synchronization for large-scale networks;

-Learning-based and bio-inspired control for complex tasks;

-Distributed optimization and parallel decision making;

-Network fault-tolerance and robustness in disturbed and uncertain environments;

-Artificial intelligence in swarm cooperative control;

-Deep learning for resource-constrained embedded vision sensor applications;

-Event-driven control strategies for silent and camouflaged unmanned systems.

Editors

  • Jinwen Hu Jinwen Hu , 

    Jinwen Hu

    Jingwen Hu is an Associate Professor at the School of Automation, Northwestern Polytechnical University, China. His research interests include sensor networks, multi-agent systems, control of multi-UAV networks, distributed filtering and control, industrial process control and big data analytics. E-Mail: hujinwen@nwpu.edu.cn

  • Jie Chen Jie Chen  &

    Jie Chen

    Jie Chen is a Professor with the School of Automation, Beijing Institute of Technology, where he serves as the Director of the Key Laboratory of Intelligent Control and Decision of Complex Systems. He also serves as the President of Tongji University. His research interests include complex systems, multiagent systems, multiobjective optimization and decision, and constrained nonlinear control. Prof. Chen is currently the Editor-in-Chief of Unmanned Systems, Autonomous Intelligent Systems, and the Journal of Systems Science and Complexity.

  • Lihua Xie Lihua Xie

    Lihua Xie

    Since 1992, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is currently Professor and Director of $25M National Research Foundation Medium Sized Centre for Advanced Robotics Technology Innovation (CARTIN) and Co-Director, Delta-NTU Corporate Laboratory for Cyber-Physical Systems.Dr. Xie’s research interests include robust control, networked control systems, multi-agent networks, indoor positioning, human activity recognition and unmanned systems. He has published 9 books, over 500 journal papers, 380 conference papers, and 20 patents/Technical Disclosures.

Articles (6 in this collection)