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Biediger, D., Mahadev, A., & Becker, A. T. 2019, Investigating the survivability of drone swarms with flocking and swarming flight patterns using virtual reality. Paper presented at 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). 
Resource type: Proceedings Article
BibTeX citation key: Biediger2019
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Categories: Artificial Intelligence, Computer Science, Decision Theory, Engineering, General
Subcategories: Autonomous systems, Drones, Machine learning
Creators: Becker, Biediger, Mahadev
Publisher:
Collection: 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)
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Abstract

It is now possible to deploy swarms of drones with populations in the thousands. There is growing interest in using such swarms for defense, and it has been natural to program them with bio-mimetic motion models such as flocking or swarming. However, these motion models evolved to survive against predators, not enemies with modern firearms. This paper presents experimental data that compares the survivability of several motion models for large numbers of drones. This project tests drone swarms in Virtual Reality (VR), because it is prohibitively expensive, technically complex, and potentially dangerous to fly a large swarm of drones in a testing environment. We model the behavior of drone swarms flying along parametric paths in both tight and scattered formations. We add random motion to the general motion plan to confound path prediction and targeting. We describe an implementation of these flight paths as game levels in a VR environment. We then allow players to shoot at the drones and evaluate the difference between flocking and swarming behavior on drone survivability.


  
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