McConville Alexander, Bose Laurie, Clarke Robert, Mayol-Cuevas Walterio, Chen Jianing, Greatwood Colin, Carey Stephen, Dudek Piotr, Richardson Tom
Flight Lab, Department of Aerospace Engineering, University of Bristol, Bristol, United Kingdom.
Visual Information Laboratory, Department of Computer Science, University of Bristol, Bristol, United Kingdom.
Front Robot AI. 2020 Sep 29;7:126. doi: 10.3389/frobt.2020.00126. eCollection 2020.
Environments in which Global Positioning Systems (GPS), or more generally Global Navigation Satellite System (GNSS), signals are denied or degraded pose problems for the guidance, navigation, and control of autonomous systems. This can make operating in hostile GNSS-Impaired environments, such as indoors, or in urban and natural canyons, impossible or extremely difficult. Pixel Processor Array (PPA) cameras-in conjunction with other on-board sensors-can be used to address this problem, aiding in tracking, localization, and control. In this paper we demonstrate the use of a PPA device-the SCAMP vision chip-combining perception and compute capabilities on the same device for aiding in real-time navigation and control of aerial robots. A PPA consists of an array of Processing Elements (PEs), each of which features light capture, processing, and storage capabilities. This allows various image processing tasks to be efficiently performed directly on the sensor itself. Within this paper we demonstrate visual odometry and target identification running concurrently on-board a single PPA vision chip at a combined frequency in the region of 400 Hz. Results from outdoor multirotor test flights are given along with comparisons against baseline GPS results. The SCAMP PPA's High Dynamic Range (HDR) and ability to run multiple algorithms at adaptive rates makes the sensor well suited for addressing outdoor flight of small UAS in GNSS challenging or denied environments. HDR allows operation to continue during the transition from indoor to outdoor environments, and in other situations where there are significant variations in light levels. Additionally, the PPA only needs to output specific information such as the optic flow and target position, rather than having to output entire images. This significantly reduces the bandwidth required for communication between the sensor and on-board flight computer, enabling high frame rate, low power operation.
在全球定位系统（GPS）信号被拒绝或降级的环境中，更普遍地说，在全球导航卫星系统（GNSS）信号被拒绝或降级的环境中，自主系统的制导、导航和控制会面临问题。这可能使在恶劣的GNSS受损环境中运行变得不可能或极其困难，比如在室内、城市峡谷和自然峡谷中。像素处理器阵列（PPA）相机与其他机载传感器配合使用，可以解决这个问题，有助于跟踪、定位和控制。在本文中，我们展示了一种PPA设备——SCAMP视觉芯片的使用，该芯片在同一设备上结合了感知和计算能力，以辅助空中机器人的实时导航和控制。PPA由一系列处理元件（PE）组成，每个处理元件都具备光捕获、处理和存储能力。这使得各种图像处理任务能够直接在传感器本身高效执行。在本文中，我们展示了视觉里程计和目标识别在单个PPA视觉芯片上以400Hz左右的组合频率同时运行。给出了室外多旋翼测试飞行的结果，并与基线GPS结果进行了比较。SCAMP PPA的高动态范围（HDR）以及以自适应速率运行多种算法的能力，使该传感器非常适合解决小型无人机在GNSS具有挑战性或信号被拒绝的环境中的室外飞行问题。HDR允许在从室内到室外环境的过渡期间以及在其他光照水平有显著变化的情况下继续运行。此外，PPA只需要输出诸如光流和目标位置等特定信息，而不必输出整个图像。这显著降低了传感器与机载飞行计算机之间通信所需的带宽，实现了高帧率、低功耗运行。
