The paper presents the design, implementation and evaluation of waveSLAM, a low-cost mobile robot system that uses the mmWave communication radios already mounted on the robot to improve indoor mapping where optical sensors struggle, such as low-visibility areas or glass and mirror walls. While the robot moves, its 60 GHz commercial off-the-shelf radios periodically exchange angle and distance estimates with each other by bouncing signals off the environment (self-sensing), and these estimates are fused with LiDAR and odometry. Experiments show centimetre-level accuracy, with errors below 22 cm and 20° in orientation, comparable to LiDAR when building indoor maps.