The DLS quadruped proprioceptive sensor dataset

Abstract

This paper presents novel datasets of the hydraulically actuated robot HyQ’s proprioceptive sensors. All of the datasets include absolute and relative joint encoders, joint force and torque sensors, and MEMS-based and fibre optic-based inertial measurement units (IMUs). Additionally, a motion capture system recorded the ground truth data with millimetre accuracy. In the datasets HyQ was manually controlled to trot in place or move around the laboratory. The sequence includes: forward and backwards motion, side-to-side motion, zig-zags, yaw motion, and a mix of linear and yaw motion. Additionally, there is motion on both rigid and soft terrain. All of the datasets are at least five minutes long and one dataset is thirty minutes long. The aim of these datasets is to test, evaluate, and compare different algorithms for state estimation using only proprioceptive sensors. To aid in the development of new state estimation algorithms for soft terrain there are datasets comparing rigid to soft terrain. Lastly, the extra long endurance trot dataset is for examining the problem of long-term attitude estimation drift. The datasets can be downloaded from https://www.doi.org/10.21227/4vxz-xw05.