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waveSLAM: Empowering accurate indoor mapping using off-the-shelf millimeter-wave self-sensing

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waveSLAM_IEEE-VTC_2023_.pdf (6.553Mb)
Identificadores
URI: https://hdl.handle.net/20.500.12761/1751
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Autor(es)
Picazo, Pablo; Groshev, Milan; Blanco, Alejandro; Fiandrino, Claudio; de la Oliva, Antonio; Widmer, Joerg
Fecha
2023-10-10
Resumen
This paper presents the design, implementation and evaluation of waveSLAM, a low-cost mobile robot system that uses the millimetre wave (mmWave) communication devices to enhance the indoor mapping process targeting environments with reduced visibility or glass/mirror walls. A unique feature of waveSLAM is that it only leverages existing Commercial-Off-The-Shelf (COTS) hardware (Lidar and mmWave radios) that are mounted on mobile robots to improve the accurate indoor mapping achieved with optical sensors. The key intuition behind the waveSLAM design is that while the mobile robots moves freely, the mmWave radios can periodically exchange angle and distance estimates between themselves (self-sensing) by bouncing the signal from the environment, thus enabling accurate estimates of the target object/material surface. Our experiments verify that waveSLAM can archive cm-level accuracy with errors below 22 cm and 20◦ in angle orientation which is compatible with Lidar when building indoor maps.
Compartir
Ficheros
waveSLAM_IEEE-VTC_2023_.pdf (6.553Mb)
Identificadores
URI: https://hdl.handle.net/20.500.12761/1751
Metadatos
Mostrar el registro completo del ítem

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