No abstract

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.

No abstract