Drone Motion Primitive Dataset

Drone technology is one of the largest tackled fields in today’s world, as it can range from pure enjoyment of drone racing to medical use and fighting crime. Several teams are interested in developing improved human machine interfaces for operating drones. This dataset is a collection of different motion primitives commanded using a PS3 joystick to control an Ardrone on Gazebo. This has been conducted using ROS Melodic on Ubuntu 18.04. The PS3 six-axis joystick was used to collect this data, and it was connected to the Gazebo drone by using the ArDrone Helpers libraries.This dataset contains 4 different motion primitives which are: Line, Helix, Sine, and Arc. The testing was conducted on each primitive alone and using a stop indicator, which is specified for each primitive, at the end of each primitive. The stop indicators are as follows:· X for Sine· Circle for Helix· Square for Line· Triangle for ArcThen a collection of every two primitives consecutively was also conducted (i.e. line to helix, arc to line, helix to sine …) using the same stop indictors at the end of every corresponding primitive. Each test has around 300 to 500 samples. It is also important to note that our data is sample and hold, meaning that if the joystick’s analog stick is in a certain position for a few seconds, then it will not send any new samples for the velocities.The data was extracted into a .YAML file, as continuous commands from the joystick which were used to move the drone in Gazebo. They are then parsed (using python 2.7) to extract the velocities of the drone along the x y z axes as well as the pressed buttons (x or circle or square or triangle) into a .CSV file.This parsed data is further processed (using python3) into another .CSV file containing all the velocities as arrays, a histogram to get the average number of samples for every sequence, and a .RTF file which contains some analysis for each primitive or collection of primitives (number of samples taken, min and max sequence size, mean, median, and deviation).N.B: for the sine primitive, the data has been extracted into two categories: one where the sine was along the x-y axes and another where it was along the x-z or y-z axes. The github link for the two codes used is: https://github.com/justinelhalabi/PS3-Joystick-Command-Parsing-into-CSV

无人机技术是当今世界所面临的诸多研究领域中最为庞大且备受瞩目的领域之一，其应用范围广泛，从纯粹的个人娱乐如无人机竞速，到医疗应用以及打击犯罪的领域。众多团队都对开发用于操作无人机的改进型人机界面表现出浓厚兴趣。本数据集汇聚了多种运动原语，这些原语是通过使用PS3手柄在Gazebo平台上控制Ardrone无人机而命令生成的。该实验在Ubuntu 18.04操作系统上使用ROS Melodic进行。实验中使用了PS3六轴手柄，并通过ArDrone Helpers库将其连接到Gazebo无人机。数据集中包含了四种不同的运动原语：直线、螺旋线、正弦波和圆弧。测试是在每种原语单独进行，并在每个原语之后使用特制的停止指示器，每个原语均有相应的指示器。停止指示器如下：X用于正弦波，圆圈用于螺旋线，正方形用于直线，三角形用于圆弧。此外，还对每两个连续原语的组合进行了测试（例如，从直线到螺旋线，从圆弧到直线，从螺旋线到正弦波等），在每个相应原语之后使用相同的停止指示器。每个测试大约包含300至500个样本。值得注意的是，我们的数据采用采样保持方式，即如果手柄的模拟杆保持在一定位置几秒钟，则不会发送任何新的样本以表示速度。数据被提取到.YAML文件中，作为连续的手柄指令，这些指令用于在Gazebo中移动无人机。随后，使用Python 2.7对这些指令进行解析，以提取无人机沿x、y、z轴的速度以及按下的按钮（x或圆圈、正方形或三角形）到.CSV文件中。该解析后的数据进一步经过处理（使用Python 3），转化为另一个.CSV文件，其中包含所有速度的数组、用于获取每个序列平均样本数的直方图，以及一个.RTF文件，其中包含对每个原语或原语集合的分析（样本数、最小和最大序列大小、平均值、中位数和偏差）。请注意：对于正弦波原语，数据被分为两类：一类是正弦波沿x-y轴，另一类是沿x-z或y-z轴。所使用的两个代码的GitHub链接为：https://github.com/justinelhalabi/PS3-Joystick-Command-Parsing-into-CSV