首页|Study Findings on Robotics Reported by Researchers at Southern University of Science and Technology (SUSTech) (Multi-View Reconstruction Fusing Ultrasonic Phased Array and Camera for Mobile Robots in Simulation Environment)
Study Findings on Robotics Reported by Researchers at Southern University of Science and Technology (SUSTech) (Multi-View Reconstruction Fusing Ultrasonic Phased Array and Camera for Mobile Robots in Simulation Environment)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
IEEE
New study results on robotics have been published. According to news reporting out of Shenzhen, People’s Republic of China, by NewsRx editors, research stated, “Distance sensors are important for mobile robots to perceive surrounding environment.” Funders for this research include Southern University of Science And Technology (Sustech) Startup Fund; Sustech-dji Joint Laboratory Fund; Shenzhen Science And Technology Project. Our news journalists obtained a quote from the research from Southern University of Science and Technology (SUSTech): “Typical sensors like LiDARs and depth cameras have been widely used, yet each has its limitations, such as LiDARs’ relatively high cost, depth cameras’ limitation to indoor use, and their poor performance in detecting transparent objects directly. On the other hand, ultrasonic phased array that integrates multiple ultrasonic sensors not only enables 3D ranging and imaging, but also provides advantages of strong environmental adaptability, being cost-effective and being able to detect transparent objects. To explore the application of in-air ultrasonic phased arrays for mobile robots, we simulate a 40 kHz $5\times 5$ non-uniform sparse ultrasonic phased array. The simulator emulates the process of phased array transmission and reception, and utilizes algorithms such as beamforming and matched filtering to obtain depth information in three-dimensional space. Then, a multi-view indoor 3D reconstruction method fusing the ultrasonic phased array and a monocular camera is proposed, where two scanning strategies are developed to handle different scenarios. Finally, the method is validated in different Gazebo scenarios and compared with other baseline methods like LiDARs and depth cameras.”
Southern University of Science and Technology (SUSTech)ShenzhenPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRobotics
NETL
NSTL
IEEE
