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This paper presents a multimodal indoor odometry dataset, OdomBeyondVision,featuring multiple sensors across the different spectrum and collected withdifferent mobile platforms. Not only does OdomBeyondVision contain thetraditional navigation sensors, sensors such as IMUs, mechanical LiDAR, RGBDcamera, it also includes several emerging sensors such as the single-chipmmWave radar, LWIR thermal camera and solid-state LiDAR. With the above sensorson UAV, UGV and handheld platforms, we respectively recorded the multimodalodometry data and their movement trajectories in various indoor scenes anddifferent illumination conditions. We release the exemplar radar,radar-inertial and thermal-inertial odometry implementations to demonstratetheir results for future works to compare against and improve upon. The fulldataset including toolkit and documentation is publicly available at:https://github.com/MAPS-Lab/OdomBeyondVision.

OdomBeyondVision: An Indoor Multi-modal Multi-platform Odometry Dataset Beyond the Visible Spectrum