移动机器人相控阵超声波雷达仿真器的设计与实现

距离传感器对于移动机器人感知周围环境十分重要，典型的距离传感器如激光雷达和深度相机已经得到了广泛应用。然而它们都有其各自的限制，激光雷达通常价格相对高昂，并且激光在雨雾、沙尘等环境中的传输容易衰减，深度相机因容易受到其他光源的干扰而被限制在室内使用，以及它们无法直接探测到玻璃等透明物体。超声波传感器具有成本低、不受恶劣环境影响、能够探测透明物体等优势，把多个超声波传感器以阵列的形式组合成的超声相控阵能够实现三维的测距和成像。但是空气中的超声相控阵因为诸多挑战仍然没有得到广泛应用，为了探究超声相控阵适用于移动机器人的可能性，本文设计并实现了一套移动机器人相控阵超声波雷达仿真器。本研究设计了一款40 kHz 5×5的非均匀稀疏超声阵列，在硬件层面上验证了超声波束的指向性、偏转和扫描功能，并在软件层面上模拟了阵列的收发过程，得到了超声相控阵生成的超声点云。此外，本研究提出了一种超声与相机融合的三维重建方法，包含面元表征和重复扫描两种策略以应对不同类型的场景。该方法在搭建的不同仿真场景中得到了验证并与激光雷达、深度相机等其他传感器进行了比较，展示了其在精度、一致性和完整性等方面的优良表现。本文在部分硬件和软件层面将声学成像应用到空气中，期待为空气中的三维成像研究和应用提供支持和新的选择。

Distance sensors are very important for mobile robots to perceive surrounding environment. Typical sensors like LiDARs and depth cameras have been widely used, yet each has its limitations. LiDARs’ are typically relatively expensive and laser transmission is prone to attenuation in rain, fog and dust, depth cameras’ limitation to indoor use due to their susceptibility to interference from other light sources, and their inability to detect transparent objects directly such as glass. Ultrasonic sensors have advantages such as low cost, resilience to harsh environments, and the capability to detect transparent objects. Combining multiple ultrasonic sensors in an ultrasonic phased array enables three-dimensional ranging and imaging. However, in-air ultrasonic phased arrays have not been widely applied due to various challenges. To explore the potential application of ultrasonic phased arrays for mobile robots, this thesis designs and implements a phased array ultrasonic radar simulator for mobile robots. This study designs a 40 kHz 5×5 non-uniform sparse ultrasonic array and validates the directivity, deflection and scanning capability of ultrasonic beams at the hardware level. Additionally, it emulates the process of phased array transmission and reception at the software level, obtaining ultrasonic point clouds generated by the ultrasonic phased array. Besides, this study proposes a three-dimensional reconstruction method fusing ultrasound and camera, including surfel characterization and repeated scanning strategies to handle different scenarios. The method is validated in different Gazebo scenarios and compared with other sensors like LiDARs and depth cameras. The experimental results reveal the method’s strong performance in terms of accuracy, consistency and completeness. This thesis applies acoustic imaging to air on both hardware and software levels, aiming to offer support and a new choice for three-dimensional imaging in the air.

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