Aerospace Controls Laboratory

Search and Rescue under the Forest Canopy using Multiple UAS

Yulun Tian


Lost hikers are often within a mile or two of the last point of detection for extended periods of time, but are undetected for hours at a time because manned aircraft cannot see through the overhead forest canopy. Small autonomous unmanned air vehicles, or drones, have been frequently proposed for search-and-rescue missions under the forest canopy. These vehicles can be rapidly deployed, can cover expanses of terrain quickly and are small enough to operate in reasonably thick forests.

We describe an experimental evaluation of a multi-vehicle UAS for search and rescue under the forest canopy. We examine the ability of multiple vehicles to carry out GPS-denied flight using laser-range finders for position estimation and map inference, plan trajectories, and fuse individual maps into a globally consistent model for exploration and search. We evaluate both a map construction process designed for search and exploration in the forest, and the corresponding search process itself.



  • Yulun Tian, Katherine Liu, Kyel Ok, Loc Tran, Danette Allen, Nicolas Roy, and Jonathan P. How, “Search and Rescue under the Forest Canopy using Multiple UAS”, International Symposium on Experimental Robotics (ISER), 2018

Related Publications

  • Tian, Y., Khosoussi, K., and How, J. P., “Resource-Aware Algorithms for Distributed Loop Closure Detection with Provable Performance Guarantees,” Proceedings of the Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018.
  • Tian, Y., Khosoussi, K., Giamou, M., How, J. P., and Kelly, J., “Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection,” Robotics: Science and Systems, 2018.
  • Giamou, M., Khosoussi, K., and How, J. P., “Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed Loop Closure Detection,” IEEE International Conference on Robotics and Automation (ICRA), 2018.
  • Khosoussi, K., Giamou, M., Sukhatme, G., Huang, S., Dissanayake, G., and How, J. P., “Reliable Graphs for SLAM,” International Journal of Robotics Research (IJRR), 2019.