Collaborative Control of Multiple UAVs for Wildfire Tracking and Monitoring

Abstract: Wildland fire fighting is a very dangerous job; the lack of information of the fire front is one of main reasons that causes many accidents. Using unmanned aerial vehicles (UAVs) to provide situational awareness for wildfire scenes is promising because it can augment human activities for hazardous fire tracking and save operation costs significantly. In this proposal we propose to study a distributed control framework designed for a team of UAVs that can closely monitor a wildfire in open space, and precisely track its development. The UAV team, designed for flexible deployment, would effectively avoid in-flight collisions as well as cooperate well with other UAV neighbors. The research team plans to conduct experimental results to demonstrate the capabilities of the UAV team in covering a spreading wildfire.

Details

  • Organization: Nevada NASA Space Grant Consortium (NVSGC)
  • Award #: NNX15AI02H
  • Amount: $30,000
  • Date: July 1, 2017 - April 9, 2018
  • PI: Dr. Hung La
  • Co-PI: Dr. David Feil-Seifer

Supported Publications

  • Pham, X. H., La, H., Feil-Seifer, D., & Nefian, A. Cooperative and distributed reinforcement learning of drones for field coverage, arXiv:1803.07250, Sep 2018. ( details )
  • Singandhupe, A., La, H., & Feil-Seifer, D. Reliable Security Algorithm for Drones Using Individual Characteristics From an EEG Signal. In IEEE Access, 6(1):22976-22986, Apr 2018. ( details ) ( .pdf )