Search and rescue under the forest canopy using multiple UAVs
Abstract
We present a multi-robot system for GPS-denied search and rescue under the forest canopy. Forests are particularly challenging environments for collaborative exploration and mapping, in large part due to the existence of severe perceptual aliasing which hinders reliable loop closure detection for mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) that perform onboard sensing, estimation, and planning. When communication is available, each UAV transmits compressed tree-based submaps to a central ground station for collaborative simultaneous localization and mapping (CSLAM). To overcome high measurement noise and perceptual aliasing, we use the local configuration of a group of trees as a distinctive feature for robust loop closure detection. Furthermore, we propose a novel procedure based on cycle consistent multiway matching to recover from incorrect pairwise data associations. The returned global data association is guaranteed to be cycle consistent, and is shown to improve both precision and recall compared with the input pairwise associations. The proposed multi-UAV system is validated both in simulation and during real-world collaborative exploration missions at NASA Langley Research Center.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 24, 2020
- Source ID
- 10.1177/0278364920929398
Entities
People
- Danette Allen
- Jonathan How
- Katherine Liu
- Kyel Ok
- Loc Tran
- Nicholas Roy
- Yulun Tian
Organizations
- Langley Research Center
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Army Research Laboratory