IMU and Servomotor Signal Dataset for Indoor Surface Classification

During data collection, the robot’s onboard IMU recorded three-axis linear acceleration and angular velocity, while servomotor sensors provided angular velocity and estimated load torque, which can be related to power consumption. The dataset contains 669 runs, each one recorded on a single surface. Of these, there are 349 runs performed using the 4W robot configuration and 320 using the 6W configuration.

This dataset was used to demonstrate that incorporating estimated power consumption features from servomotors can improve IMU-based classification accuracy. The data is suitable for applications such as terrain-aware navigation, adaptive control, slip detection, and energy-efficient path planning. The corresponding code (data processing and model training) can be found in the paper respository: github.com/lukasz-kedzierski/surface-classification