The perception group research focuses on the development of state estimation for quadruped robots. The typical state of a robot includes its position, orientation, and velocity. However, the state can also include many diverse quantities such as simultaneous localization and mapping (SLAM) and ground reaction forces. State estimation is an essential step to any control problem and its difficulty is often underestimated.


Current perception sensors include:

  • Lidars - for large scale navigation and obstacle avoidance
  • Colour Cameras - for path planning localization and mapping in indoor/outdoor operations, and semantic mapping.
  • Depth Cameras - for foothold planning, localization and mapping in indoor conditions
  • Force/Torque Sensors – for measuring joint effort and ground reaction forces
  • Encoders – for measuring joint angle and speed

The main tasks of the perception system are:

  • State estimation
  • Simultaneous Localization And Mapping (SLAM)
  • Visual inertial SLAM
  • Vision based terrain Modeling for locomotion with foothold planning (accurate 3D model, traversability map including the terrain type)
  • Terrain/obstacle classification for semantic mapping
  • Object recognition and manipulation
  • Visual servoing
  • Automatic sensor calibration

proprioceptive dataset

Proprioceptive sensor dataset for quadruped robots

These datasets are of the hydraulically actuated robot HyQ’s proprioceptive sensors. They include absolute and relative encoders, 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. All of the datasets are at least five minutes long. The aim of these datasets is to test state estimation using only proprioceptive sensors.
Link to dataset