  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 20deg in angle orientation which is compatible with Lidar when
building indoor maps.
