Energy consumption data for package delivery with an Uncrewed Ground Vehicle

The purpose of this experiment was to empirically measure the energy use of uncrewed ground vehicles (UGVs) carrying a range of payloads on different routes, terrains, temperatures and speeds. We manually operated a modified Husky A200 robot platform (Husky) on four different routes, which differ both in total distance and vertical gradient. We simultaneously collected data from a broad range of sensors on the Husky.<br>The onboard sensors used to collect data on the Husky are:* Position: 3DM-GX5-45 GNSS/INS sensor pack. These sensors use a built-in Kalman filtering system to fuse the GPS and IMU data. The sensor has a maximum output rate of 10Hz.* Current and Voltage: Mauch Electronics PL-200 sensor. This sensor can record currents up to 200 A and voltages up to 33 V. Analogue readings from the sensor were converted into a digital format using an 8 channel 17 bit analogue-to-digital converter (ADC).* Temperature and humidity: Bosch BME280 sensor. The sensor measures relative humidity with ±3% accuracy, and temperature with ± 1.0°C accuracy. The ideal operating range for this sensor is 0°C to 65°C.<br>An on-board computer was used to operate the Husky and post-process the data. The on-board computer was an Intel NUC Kit NUC8i7BEH with a 512 GB solid state drive (SSD) and 8 GB of memory. This computer ran the Melodic distribution of the Robotic Operating System (ROS), on top of Ubuntu 18.04 LTS operating system. Data syncing and recording was enabled through ROS running on a low-power Raspberry Pi Zero W. The Raspberry Pi's microSD card served as the data store. The data streams from each sensor were synchronized to a frequency of approximately 10Hz using the ApproximateTime message filter policy of Robot Operating System (ROS).<br>There are a total of 92 trials across varying routes, payloads and speeds. The concatenated dataset has 386,369 rows of data and 27 columns.

本实验旨在通过实证方法，测量无人地面车辆（Uncrewed Ground Vehicles, UGVs）在不同路线、地形、温度及行驶速度下，搭载多种载荷时的能耗水平。我们手动操控一台经过改装的Husky A200机器人平台（后文简称Husky），在4条总里程与垂直坡度均存在差异的路线上开展实验，并同步采集Husky搭载的多款传感器的相关数据。

Husky搭载的用于数据采集的板载传感器如下：
- 位置数据：3DM-GX5-45 GNSS/INS组合传感器套件。该传感器内置卡尔曼滤波系统，可融合GPS与惯性测量单元数据，最大输出速率为10Hz。
- 电流与电压数据：Mauch Electronics PL-200传感器。该传感器可测量最高200A的电流与最高33V的电压，其模拟读数通过8通道17位模数转换器（Analogue-to-Digital Converter, ADC）转换为数字格式。
- 温湿度数据：Bosch BME280传感器。该传感器可测量相对湿度（测量精度±3%）与环境温度（测量精度±1.0℃），理想工作温度范围为0℃至65℃。

本实验使用一台机载计算机操控Husky并对采集到的数据进行后处理，该计算机为Intel NUC Kit NUC8i7BEH，搭载512GB固态硬盘（Solid State Drive, SSD）与8GB内存。该计算机在Ubuntu 18.04 LTS操作系统之上运行机器人操作系统（Robotic Operating System, ROS）的Melodic发行版。此外，我们通过运行于低功耗树莓派Zero W上的ROS实现数据同步与记录，树莓派的microSD卡作为数据存储介质。利用机器人操作系统（ROS）的ApproximateTime消息过滤策略，将各传感器的数据流同步至约10Hz的采样频率。

本实验共开展92组涵盖不同路线、载荷与行驶速度的测试。合并后的数据集共包含386369条数据记录，涵盖27个数据字段。