planetary navigation
Decentralized Collaborative Simultaneous Localization and Mapping (C-SLAM) is essential to enable multi-robot missions in unknown environments without relying on pre-existing localization and communication infrastructure. This technology is anticipated to play a key role in the exploration of the Moon, Mars, and other planets. In this work, we introduce a novel dataset collected during C-SLAM experiments involving three robots operating on a Mars analogue terrain.
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This is a unique energy-aware navigation dataset collected at the Canadian Space Agency’s Mars Emulation Terrain (MET) in Saint-Hubert, Quebec, Canada. It consists of raw and post-processed sensor measurements collected by our rover in addition to georeferenced aerial maps of the MET (colour mosaic, elevation model, slope and aspect maps). The data are available for download in human-readable format and rosbag (.bag) format. Python data fetching and plotting scripts and ROS-based visualization tools are also provided.
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