Sixth Sense: Indoor Human Spatial Awareness Dataset

The Sixth Sense: Indoor Human Spatial Awareness Dataset comprises sensor recordings from a custom version of PAL Robotics TIAGo equipped with two 1D planar LiDARs, an Azure Kinect camera for human detections. The dataset was collected over nine days in three distinct indoor environments, capturing human activity and spatial interactions.Data Collection EnvironmentsUniversity Corridor: A public transit area between classrooms with study desks and passersby (36k samples). The robot's motion was manually controlled for safety reasons.Break Area: A large indoor space with tables and chairs where expert individuals interact with the robot (12k samples). The robot followed autonomous, randomized trajectories while avoiding obstacles.Lab: A controlled laboratory environment where expert individuals interact with the robot (7k samples). This setup includes high-precision ground truth tracking from an OptiTrack motion capture system.Data SplitsIn the original paper the dataset was diveded as follows:Training Set: All University Corridor samples and half of Break Area samples (42k samples).Validation Set: The remaining half of Break Area samples (6k samples).Test Set: All Lab samples (7k samples).

第六感：室内人体空间感知数据集包含来自PAL Robotics TIAGo定制版本的传感器记录，该机器人配备了两个一维平面激光雷达（LiDAR）以及用于人体检测的Azure Kinect相机。该数据集在三个不同的室内环境中历时九天采集而成，记录了人体活动与空间交互。

数据采集环境
大学走廊：位于教室之间的公共通行区域，设有学习桌并有人流经过（36000个样本）。出于安全考虑，机器人的运动采用手动控制。

休息区：配备桌椅的大型室内空间，由专业人员与机器人进行交互（12000个样本）。机器人在避障的同时遵循自主随机轨迹移动。

实验室：专业人员与机器人交互的受控实验环境（7000个样本）。该场景包含来自OptiTrack动作捕捉系统的高精度真实轨迹（ground truth）跟踪数据。

数据划分
在原始论文中，数据集的划分如下：

训练集：所有大学走廊样本及一半休息区样本（42000个样本）。

验证集：休息区剩余的一半样本（6000个样本）。

测试集：所有实验室样本（7000个样本）