Localization and Control for Unmanned Autonomous Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 62
Special Issue Editor
Interests: localization; control; physical AI; SLAM; unmanned autonomous systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As unmanned autonomous systems increasingly interact with and operate within the physical world, precise positioning and robust control have become core requirements for achieving reliable and safe autonomy. The emergence of Physical AI, which integrates perception, positioning, decision-making, and control with real-world physical constraints, has further highlighted the importance of accurate localization and state estimation as foundational components of autonomous intelligence.
Recent research has demonstrated significant progress in positioning and localization technologies for unmanned systems, driven by advances in sensing, sensor fusion, and learning-based approaches. These include GNSS-denied positioning, SLAM and simultaneous positioning and mapping, vision- and RF-based localization, and cooperative and distributed positioning, as well as multi-modal fusion of inertial, visual, radio, and range sensors. When combined with adaptive, robust, and learning-based control strategies, these techniques enable autonomous systems to perceive their environment, estimate their states, and interact with the physical world in a closed-loop and embodied manner. Nevertheless, challenges remain in terms of robustness, scalability, real-time deployment, and generalization across complex and dynamic environments.
This Special Issue aims to bring together recent advances in positioning, localization, and control for unmanned autonomous systems, with a particular focus on Physical AI and embodied intelligence. Contributions may address theoretical foundations, algorithmic developments, experimental validation, and real-world applications that advance the integration of positioning-aware perception and control for next-generation autonomous systems.
Dr. Jaehyun Yoo
Guest Editor
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Keywords
- physical AI
- positioning and localization
- sensor fusion
- SLAM
- learning-based control
- embodied autonomous systems
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