Research Topic

AI for Autonomous Unmanned Systems

About this Research Topic

In recent decades, autonomous unmanned systems have received increasingly significant attention due to their potential to enhance unmanned system intelligence, unmanned system performance, and unmanned system efficiency. One of the key objectives of autonomous unmanned systems is to realize a high degree of autonomy under dynamic, complex environments. From multi-disciplinary perspectives including robotics, computer vision, artificial intelligence, control theory, etc., significant research efforts have been devoted to improving the performance of autonomous perception, situation awareness, decision-making and control abilities for autonomous unmanned systems. However, due to the uncertainties and complexities of real-world environments, objects and obstacles are dynamic, making it a necessity for autonomous unmanned systems to further improve abilities such as online learning, unmanned systems skill learning from past experiences, situation awareness, trajectory planning, decision-making and motion control.

This Research Topic will include a collection of outstanding technical research oriented tutorials or surveys, high level position papers and new research results, covering a wide range of topics within autonomous unmanned systems intelligent perception, situation awareness, decision-making and motion control.

The goal is to address the following technical challenges: (i) to rapidly and accurately detect, recognize and track dynamic objects under complex conditions, (ii) to build accurate maps and realize self-localization in uncertain, dynamic environments, (iii) to implement motion planning and avoid dynamic obstacles with multiple goals such as safety, agility, and efficiency, (iv) to learn from past experience and reuse the learned knowledge to continually improve autonomous unmanned systems performance, and (v) to effectively communicate with each other for sharing of information.


  • Intelligent Perception for autonomous unmanned systems

    • Real-time object detection, recognition, and tracking for autonomous unmanned systems.

    • Deep learning methods for real-time perception of autonomous unmanned systems.

    • Reinforcement learning methods for real-time perception of autonomous unmanned systems.

  • Intelligent decision-making for autonomous unmanned systems

    • Map building and localization of autonomous unmanned systems.

    • Motion planning of autonomous unmanned systems.

    • Situational assessment for autonomous unmanned systems.

    • Intelligent decision-making for autonomous unmanned systems.

    • End to End Learning for autonomous unmanned systems.

  • Intelligent control for autonomous unmanned systems

    • Autonomous unmanned systems cyber-physical systems.

    • Intelligent cooperative control of autonomous unmanned systems.

    • Intelligent path tracking and motion control for autonomous unmanned systems.

    • Intelligent longitudinal control for autonomous unmanned systems.

    • Intelligent lateral control for autonomous unmanned systems.

    • Reinforcement learning methods for autonomous control of autonomous unmanned systems.

    • Deep learning methods for autonomous control of autonomous unmanned systems.


Keywords: Artificial intelligence (AI), Autonomous Unmanned Systems, Intelligent Perception, Decision-making, Reinforcement learning, Deep learning


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

In recent decades, autonomous unmanned systems have received increasingly significant attention due to their potential to enhance unmanned system intelligence, unmanned system performance, and unmanned system efficiency. One of the key objectives of autonomous unmanned systems is to realize a high degree of autonomy under dynamic, complex environments. From multi-disciplinary perspectives including robotics, computer vision, artificial intelligence, control theory, etc., significant research efforts have been devoted to improving the performance of autonomous perception, situation awareness, decision-making and control abilities for autonomous unmanned systems. However, due to the uncertainties and complexities of real-world environments, objects and obstacles are dynamic, making it a necessity for autonomous unmanned systems to further improve abilities such as online learning, unmanned systems skill learning from past experiences, situation awareness, trajectory planning, decision-making and motion control.

This Research Topic will include a collection of outstanding technical research oriented tutorials or surveys, high level position papers and new research results, covering a wide range of topics within autonomous unmanned systems intelligent perception, situation awareness, decision-making and motion control.

The goal is to address the following technical challenges: (i) to rapidly and accurately detect, recognize and track dynamic objects under complex conditions, (ii) to build accurate maps and realize self-localization in uncertain, dynamic environments, (iii) to implement motion planning and avoid dynamic obstacles with multiple goals such as safety, agility, and efficiency, (iv) to learn from past experience and reuse the learned knowledge to continually improve autonomous unmanned systems performance, and (v) to effectively communicate with each other for sharing of information.


  • Intelligent Perception for autonomous unmanned systems

    • Real-time object detection, recognition, and tracking for autonomous unmanned systems.

    • Deep learning methods for real-time perception of autonomous unmanned systems.

    • Reinforcement learning methods for real-time perception of autonomous unmanned systems.

  • Intelligent decision-making for autonomous unmanned systems

    • Map building and localization of autonomous unmanned systems.

    • Motion planning of autonomous unmanned systems.

    • Situational assessment for autonomous unmanned systems.

    • Intelligent decision-making for autonomous unmanned systems.

    • End to End Learning for autonomous unmanned systems.

  • Intelligent control for autonomous unmanned systems

    • Autonomous unmanned systems cyber-physical systems.

    • Intelligent cooperative control of autonomous unmanned systems.

    • Intelligent path tracking and motion control for autonomous unmanned systems.

    • Intelligent longitudinal control for autonomous unmanned systems.

    • Intelligent lateral control for autonomous unmanned systems.

    • Reinforcement learning methods for autonomous control of autonomous unmanned systems.

    • Deep learning methods for autonomous control of autonomous unmanned systems.


Keywords: Artificial intelligence (AI), Autonomous Unmanned Systems, Intelligent Perception, Decision-making, Reinforcement learning, Deep learning


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

02 November 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

02 November 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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