QCAT legged robot terrain classification dataset

The dataset includes measurements from two different sensor types on the quadruped robot DyRET. A 3-axis force sensor is mounted on the end of each of the four legs (Optoforce OMD-20-SH-80N), referred to as 'raw' in the dataset. The robot also has an Inertial Measurement Unit (IMU) mounted (Xsens MTI-30). It contains a 3-axis gyroscope providing rotational velocities, a 3-axis accelerometer providing linear accelerations, and a 3-axis magnetometer providing absolute orientation in reference to the Earth's magnetic field. The data is labeled 'imu' in the dataset. The robot walks forward on 6 different surfaces, available in the 'surface' column (0: Concrete, 1: Grass, 2: Gravel, 3: Mulch, 4: Dirt, 5: Sand). It does so at 6 different speeds, available in the 'speed' column (0-1: frequency 0.125 Hz; 1-2: frequency 0.1875 Hz; 3-4: frequency 0.25 Hz; 0,2,4: step length 80 mm; 1,3,5: step length 120 mm). There are 10 trials in each file (available in the 'eval_id' column) with 8 steps for each trial. This gives a total of 6*10*6*8 = 2880 steps in total. The jupyter notebook source code used for processing the force sensor data and IMU data is provided.\n\nLineage: The QCAT dataset was collected at different locations on CSIRO’s QCAT site in Brisbane, Australia, in November 2019 using the quadruped robot DyRET. The different environments comprising the data set are 1. Concrete road, 2.Grass, 3. Gravel, 4. Mulch, 5. Dirt path, and 6. Sand. \nData collection was done by walking with a fixed gait, but with three different step frequencies (0.125 Hz, 0.1875 Hz and 0.25 Hz) and two different step lengths (80 mm and 120 mm), for a total of six different speeds tested per surface. The robot walks forwards for ten trials of eight steps per speed and surface. A total of 2880 steps are available in the dataset. To be representative of the terrain type and reduce impact of local variation, each repetition was performed on a different part of the terrain.

本数据集包含四足机器人DyRET搭载的两类传感器的测量数据。其一为三轴力传感器（Optoforce OMD-20-SH-80N），安装于四条机械腿的末端，该类数据在数据集中标记为“raw”；其二为型号为Xsens MTI-30的惯性测量单元（Inertial Measurement Unit, IMU），该单元集成三轴陀螺仪（用于获取旋转角速度）、三轴加速度计（用于获取线加速度）以及三轴磁强计（用于获取基于地球磁场的绝对姿态），此类数据在数据集中标记为“imu”。
该机器人可在6类不同地表表面上向前行走，地表类型可通过数据集中的“surface”列查询：0代表混凝土路面，1代表草地，2代表碎石路面，3代表覆盖物步道，4代表泥土路，5代表沙地。行走速度共设6种组合，可通过数据集中的“speed”列查询：0-1档对应步频0.125 Hz；1-2档对应步频0.1875 Hz；3-4档对应步频0.25 Hz；其中0、2、4档的步长为80 mm，1、3、5档的步长为120 mm。
每个数据文件包含10组试验（可通过“eval_id”列区分每组试验），每组试验包含8个行走步距。综上，本数据集总计包含6×10×6×8=2880个有效步距数据。同时附带了用于处理力传感器数据与IMU数据的Jupyter Notebook源代码。
数据谱系：本QCAT数据集于2019年11月在澳大利亚布里斯班的CSIRO QCAT试验场不同区域采集完成，搭载的四足机器人为DyRET。数据集涵盖的实验环境共6类：1. 混凝土路面、2. 草地、3. 碎石路面、4. 覆盖物步道、5. 泥土路以及6. 沙地。
数据采集采用固定步态，设置了3种不同步频（0.125 Hz、0.1875 Hz与0.25 Hz）与2种不同步长（80 mm与120 mm），因此每种地表表面可对应6种不同的行走速度组合。针对每种速度与地表组合，机器人完成10组试验，每组试验包含8个行走步距。为确保数据能充分代表对应地表类型并降低局部地形差异的影响，每组试验均在该地形的不同区域完成。本数据集总计包含2880个有效步距数据。