Intelligent and Dynamic Control of Mobile, Aerial, and Underwater Robots
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 February 2025 | Viewed by 1039
Special Issue Editors
Interests: mobile robots; Kalman filters; aircraft control; autonomous underwater vehicles
Interests: reconfigurable modular robots; decentralized control; distributed planning; excessive disturbance attenuation; transfer reinforcement learning
Special Issues, Collections and Topics in MDPI journals
Interests: deep reinforcement learning; convolutional neural networks; variational autoencoders
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The field of robotics is undergoing a transformative phase, with mobile, aerial, and underwater robots playing a pivotal role in various applications, from industrial automation to healthcare and beyond. In recent years, mobile, aerial, and underwater robots have become integral to diverse sectors, demanding sophisticated control mechanisms to navigate complex and dynamic terrains. The dynamic nature of real-world environments poses challenges that necessitate intelligent control strategies for mobile, aerial, and underwater robots. The fusion of intelligent algorithms and dynamic control strategies holds the key to enhancing the efficiency, adaptability, and safety of mobile, aerial, and underwater robots in a wide range of applications.
This Special Issue aims to explore and showcase the latest advancements in the intelligent and dynamic control of mobile, aerial, and underwater robots, addressing the pressing need for adaptive and responsive robotic systems. This Special Issue invites contributions that delve into the intelligent and dynamic control of mobile, aerial, and underwater robots.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Real-time decision-making strategies for mobile, aerial, and underwater robots;
- Adaptive control approaches for mobile, aerial, and underwater robots;
- Machine learning approaches for robot planning and control;
- Navigation and path planning in dynamic and unstructured environments;
- Multi-robot coordination and collaboration;
- Human–robot interaction for enhanced control;
- Applications of mobile, aerial, and underwater robots.
We look forward to receiving your contributions.
Dr. Hao Xiong
Dr. Wenjie Lu
Dr. Lin Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- mobile robots
- aerial robots
- autonomous underwater vehicles
- cooperative robots
- intelligent control
- intelligent navigation and planning
- learning-based planning and control
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