Research Topic

Multi-Swarms of Unmanned Autonomous Systems

About this Research Topic

Swarms of Unmanned Autonomous Systems (UAS), usually inspired by nature, such as bird flocks or fish schools, have been introduced to achieve complex common objectives through collaborative behaviors. Swarms have already been intensively studied as a way to address the limitations of single autonomous systems by augmenting the range of action, increasing the resilience and flexibility of UAS systems. These properties make them very suitable for numerous applications like surveillance, search and rescue or wide-area monitoring.

Going one step further, the usage of multiple swarms of different types of autonomous vehicles, e.g. Unmanned Aerial Vehicles (UAV) or Unmanned Ground Vehicles (UGV) recently gained attention. Multi-swarm systems can be composed of heterogeneous vehicles moving in an autonomous and coordinated way, for instance in the air, on the ground, or in the sea. While members of a single swarm work collectively to achieve a mission, interactions between swarms can similarly be cooperative but also competitive (e.g., swarms vs. swarms), opening new research challenges.

Multi-swarm systems remain an open research topic because of the intrinsic difficulty in obtaining efficient global behavior while relying on local decisions from distributed and heterogeneous entities evolving in different swarms. Such highly dynamical networked systems not only require efficient mobility behaviors, but also optimized ad hoc communications within and between swarms.

The development of UAS swarming solutions is still mainly limited to manual design and optimization, which becomes increasingly tedious and hardly scalable when considering multi-swarm systems. Therefore, novel artificial intelligence (AI) and optimization approaches are thus required to allow the development of efficient multi-swarm behaviors.

In order to disseminate the current advances in multi-swarm systems of UAS, we seek submissions describing novel work for a Research Topic in this area.
• Multi-swarm mobility models
• Multi-swarm simulations
• Multi-swarm testbeds
• Multi-swarm networking models and optimization (e.g., multi-layer networks)
• Heuristics - meta-heuristics (GP and RL as methodologies) for multi-swarm optimization
• Machine learning for multi-swarm systems
• Models for UTM (UAV Traffic Management)
• Prey-Predator dynamics in multi-swarms
• Multi-swarm collaborative models
• Game theoretical models
• Multi-swarm applications: surveillance, defense, intruder detection and handling
• State-of-the-art analysis (on the topics above)


Keywords: UAS, Swarm intelligence, Artificial intelligence, Optimization, Nature inspired techniques


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.

Swarms of Unmanned Autonomous Systems (UAS), usually inspired by nature, such as bird flocks or fish schools, have been introduced to achieve complex common objectives through collaborative behaviors. Swarms have already been intensively studied as a way to address the limitations of single autonomous systems by augmenting the range of action, increasing the resilience and flexibility of UAS systems. These properties make them very suitable for numerous applications like surveillance, search and rescue or wide-area monitoring.

Going one step further, the usage of multiple swarms of different types of autonomous vehicles, e.g. Unmanned Aerial Vehicles (UAV) or Unmanned Ground Vehicles (UGV) recently gained attention. Multi-swarm systems can be composed of heterogeneous vehicles moving in an autonomous and coordinated way, for instance in the air, on the ground, or in the sea. While members of a single swarm work collectively to achieve a mission, interactions between swarms can similarly be cooperative but also competitive (e.g., swarms vs. swarms), opening new research challenges.

Multi-swarm systems remain an open research topic because of the intrinsic difficulty in obtaining efficient global behavior while relying on local decisions from distributed and heterogeneous entities evolving in different swarms. Such highly dynamical networked systems not only require efficient mobility behaviors, but also optimized ad hoc communications within and between swarms.

The development of UAS swarming solutions is still mainly limited to manual design and optimization, which becomes increasingly tedious and hardly scalable when considering multi-swarm systems. Therefore, novel artificial intelligence (AI) and optimization approaches are thus required to allow the development of efficient multi-swarm behaviors.

In order to disseminate the current advances in multi-swarm systems of UAS, we seek submissions describing novel work for a Research Topic in this area.
• Multi-swarm mobility models
• Multi-swarm simulations
• Multi-swarm testbeds
• Multi-swarm networking models and optimization (e.g., multi-layer networks)
• Heuristics - meta-heuristics (GP and RL as methodologies) for multi-swarm optimization
• Machine learning for multi-swarm systems
• Models for UTM (UAV Traffic Management)
• Prey-Predator dynamics in multi-swarms
• Multi-swarm collaborative models
• Game theoretical models
• Multi-swarm applications: surveillance, defense, intruder detection and handling
• State-of-the-art analysis (on the topics above)


Keywords: UAS, Swarm intelligence, Artificial intelligence, Optimization, Nature inspired techniques


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

28 February 2020 Abstract
15 June 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

28 February 2020 Abstract
15 June 2020 Manuscript

Participating Journals

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

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