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Integrating drones into construction sites can introduce new risks to workers who already work in hazardous environments. Consequently, several recent studies have investigated the safety challenges and solutions associated with this technology integration in construction. However, there is a knowledge gap about effectively communicating such safety challenges to construction professionals and students who may work alongside drones on job sites. In this study, a 360-degree virtual reality (VR) environment was created as a training platform to communicate the safety challenges of worker-drone interactions on construction jobsites. This pilot study assesses the learning effectiveness and user experience of the developed 360 VR worker-drone safety training, which provides an immersive device-agnostic learning experience. The result indicates that such 360 VR learning material could significantly increase the safety knowledge of users while delivering an acceptable user experience in most of its assessment criteria. The outcomes of this study will serve as a valuable resource for improving future worker-drone safety training materials.
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Investigating the survivability of drone swarms with flocking and swarming flight patterns using Virtual Reality
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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- PAR ID:
- 10130229
- Date Published:
- Journal Name:
- International Conference on Automation Science and Engineering (IEEE CASE 22-26 August 2019, Vancouver, Canada)
- Page Range / eLocation ID:
- 1718 to 1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/COASE.2019.8843173
