The ultrasonic sensors are widely used for vehicles to extract obstacles in the scene. They can obtain the distance to the object directly at a low cost even in harsh environments. However, since the information from a single ultrasonic sensor is very limited, it has not been used for recovering the detailed 3D structure and semantic labels of the scene, unlike in-vehicle cameras or LiDARs. Therefore, we in this paper propose a method for recovering the dense 3D structure and semantic labels of the scene from a moving ultrasonic sensor mounted on a vehicle. Our method uses the raw profiles of the ultrasonic sensor signals and learns the relationship between the raw ultrasonic signals and the 3D scene using multi-task learning. As a result, our method can recover the dense 3D structure and semantic labels of the scene similar to what we would recover with cameras and LiDARs just from a single moving ultrasonic sensor. The efficiency of the proposed method is tested using real sensor data as well as synthetic sensor data.
Seeing Nearby 3D Scenes using Ultrasonic Sensors
2022 IEEE Intelligent Vehicles Symposium (IV) ; 1387-1392
05.06.2022
1277326 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Seeing With Sound — Next-level 3D ultrasonic sensors based on echolocation
British Library Conference Proceedings | 2019
|British Library Conference Proceedings | 2016
|Digital Image Synthesizers: Are Enemy Sensors Really Seeing What's There?
Online Contents | 2006
|