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We present a multi-robot system for GPS-denied search and rescue under theforest canopy. Forests are particularly challenging environments forcollaborative exploration and mapping, in large part due to the existence ofsevere perceptual aliasing which hinders reliable loop closure detection formutual localization and map fusion. Our proposed system features unmannedaerial vehicles (UAVs) that perform onboard sensing, estimation, and planning.When communication is available, each UAV transmits compressed tree-basedsubmaps to a central ground station for collaborative simultaneous localizationand mapping (CSLAM). To overcome high measurement noise and perceptualaliasing, we use the local configuration of a group of trees as a distinctivefeature for robust loop closure detection. Furthermore, we propose a novelprocedure based on cycle consistent multiway matching to recover from incorrectpairwise data associations. The returned global data association is guaranteedto be cycle consistent, and is shown to improve both precision and recallcompared to the input pairwise associations. The proposed multi-UAV system isvalidated both in simulation and during real-world collaborative explorationmissions at NASA Langley Research Center.

Search and Rescue under the Forest Canopy using Multiple UAVs