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Estimating Altitude of Drones Using Batteries

机译:使用电池估算无人机的高度

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摘要

With the rise of drone technology, both new possibilities and new problems are presented in an expanding variety of applications. One such application is the use of drones to establish temporary mobile networks over a small area in the event of a catastrophe or environmental disaster, however this may require establishing the location of a drone without GPS data or other location sensors. In such cases, external battery readings may be used to characterize drone behavior and predict its location. Alternatively, to defend against cyberattacks drone battery data may be used as an authentication method by verifying internal sensor readings against separate measurements from an external system, validating of internal readings and detecting abnormalities. By analyzing certain characteristics of battery current draw and voltage readings, specific drone behaviors can be determined or predicted. The focus of this research study is to determine what classifications or predictions of drone flight behavior may be made using external battery readings alone, and to explore if the problems outlined above are solvable through this method. Data was collected using a DJI Mavic Air drone with an externally attached microcontroller over a series of controlled flight patterns. Internal sensor readings from the DJI Mavic Air drone, including altitude and acceleration, are stored in onboard flight logs and were used to validate the externally measured data. Battery readings were taken externally using an Arduino-based system that bridges the physical connection between the battery and the drone body, measuring and logging the cumulative current draw and voltage of the battery while the drone is in flight. From this data we were able to develop programs to accurately classify the drone state as being in takeoff, hovering, ascending, descending, or landing. We were also able to find a relationship mapping cumulative battery current draw to acceleration. Using the detected flight state in conjunction with the calculated acceleration, our program is able to accurately estimate the altitude of the drone using only externally measured cumulative battery current.
机译:随着无人机技术的兴起,在扩大各种应用中,展示了新的可能性和新问题。一个这样的应用是在发生灾难或环境灾难时使用无人机在一个小面积上建立临时移动网络,但是这可能需要建立没有GPS数据或其他位置传感器的无人机的位置。在这种情况下,外部电池读数可用于表征无人机行为并预测其位置。或者,为了防御Cyber​​Actacks无人机电池数据可以通过验证来自外部系统的单独测量的内部传感器读数来用作认证方法,验证内部读数并检测异常。通过分析电池电流抽取和电压读数的某些特性,可以确定或预测特定的无人机行为。该研究的重点是确定无人机飞行行为的分类或预测可以单独使用外部电池读数,并探索上述问题是否通过该方法可解决。使用DJI Mavic Air无人机收集数据,其外部附加的微控制器通过一系列受控飞行模式。来自DJI Mavic Air无人机的内部传感器读数,包括高度和加速,存储在板载飞行日志中,用于验证外部测量数据。使用基于Arduino的系统外部采用电池读数,该系统桥接电池和无人机主体之间的物理连接,测量和记录电池的累积电流抽取和电池电压,而无人机在飞行中。从该数据来看,我们能够开发程序,以准确地将无人机状态分类为起飞,悬停,升序,下降或降落。我们还能够找到一种关系映射累积电池电流抽取的加速。使用检测到的飞行状态与计算的加速度结合使用,我们的程序能够仅使用外部测量的累积电池电流准确地估计无人机的高度。

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