REU: Adaptive Sonar Sensing

声纳是机器人的一种有吸引力的传感方式，因为它相对简单的实现和处理，具有低成本和低能耗，可以与相机视觉结合使用，并且对于某些应用来说，它是唯一实用的传感方式。本研究探讨一种自适应声纳感测的形式，其中传感器在感测过程中改变其物理配置以响应所观察到的回波。 这种方法类似于主动计算机视觉的一些方法，其动机是生物系统将耳朵转向声源的方向并移动以从不同方向观察物体。作为这项研究的一部分，信号处理算法进行了研究，以开发一个传感系统，可以识别对象的声学签名。目前的回声产生模型扩展到预测声纳系统观察到的回声。声纳允许机器人精确地在非结构化环境中导航，并通过使用环境对象作为自然发生的信标来构建精确的声纳地图。 这种方法应该支持移动的机器人和机器人手臂的更自主和灵活的操作，从而提高它们在制造应用中的功能。

Sonar is an attractive sensing modality for robotics because it is relatively simple to implement and process, has low cost and energy consumption, can be used in conjunction with camera vision, and for some applications it is the only practical sensing modality. This research investigates a form of adaptive sonar sensing, in which the sensor changes its physical configuration during the sensing process in reaction to the observed echoes. This approach, analogous to some approaches to active computer vision, is motivated by biological systems that turn their ears toward the direction of the sound source and move to observe an object from different directions. As part of this research, signal processing algorithms are investigated to develop a sensing system that can identify objects by their acoustic signatures. The current model of echo production is extended to predict the echoes observed by the sonar system. The sonar allows the robot to navigate around an unstructured environment precisely and to construct accurate sonar maps by using environmental objects as naturally-occurring beacons. This approach should support more autonomous and flexible operation of both mobile robots and robot arms, thus improving their functionality in manufacturing applications.