NICOP - HUNTED - Heterogeneous multi-swarms of UNmanned auTonomous systEms for mission Deployment

Abstract

The HUNTED project (Heterogeneous multi-swarms of UNmanned auTonomous systEms formission Deployment) aims at designing a novel generation of mobility models forheterogeneous multi-swarms of Unmanned Autonomous Systems (UAS) for surveillanceand tracking of imminent threats. Such swarms are composed of several vehicles moving in anautonomous and coordinated manner in the air, on the ground, and in the sea. Each of them canembed different sensors (e.g., video, infrared, radar) ensuring complementarity and resilience.While the UAS are conducting their mission in a fully autonomous manner, connectivity to one ormultiple base stations is optimized which will ensure an efficient and reliable collection of data forfurther post processing and decision making by the ground forces.Emerging artificial intelligence approaches sparked a new revolution in terms of autonomousbehaviours. However, few of these techniques have been employed to create intelligentmobility models for UAS, especially when considering heterogeneous devices. It is known thatspecies organized as swarms develop a collective intelligence making them more able to survivein hostile environments.The HUNTED project therefore aims at developing novel and highly efficient nature inspiredmechanisms hybridized with chaos theory and clustering techniques for the efficient mobilitymanagement of heterogeneous swarms of UAS in a fully distributed way for different types ofmissions. These disruptive models will be designed, and their performance validated andevaluated using a comprehensive three steps approach, (1) high-level theoretical simulations, (2)physical simulations, and (3) real field tests.These models will stand out thanks to a first of its kind integration of state-of-the-art solutions thatwill permit to optimize the missions??? objectives and resilience while ensuring unpredictable yetdeterministic trajectories in the different swarm levels.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 19, 2018
Source ID
N629091812176

Entities

People

  • Pascal Bouvry

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Luxembourg

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control