TacTID: High-Performance Visuo-Tactile Sensor-Based Terrain Identification for Legged Robots

Adapting to various terrains and improving locomotion performance have always been challenging for legged robots. Inspired by the animal somatosensory system in walking and balancing, the robot can benefit from the foot sensors as well when interacting with the terrain and gain better performance. In this article, we propose a visuo-tactile foot sensor with embedded markers, named TacTID, for legged robot terrain identification. By introducing elastic embedded markers on an elastic hemispherical shell, TacTID could detect 3-D pressure distribution directly, based on which the terrain coefficient of sliding friction (COSF) and terrain effective stiffness can be estimated precisely. The results of the COSF prediction experiment demonstrate that TacTID exhibits an average error of 0.036, which is notably lower than that of TacTip. For the effective stiffness estimation experiment, TacTID is tested on ten silicone cubes with different Young's moduli, and the absolute average estimation error is less than 0.1 MPa. Besides, a quadruped robot is equipped with TacTID for real-time terrain identification, and the possibility to estimate COSF and the terrain effective stiffness in various terrains is demonstrated. This research highlights the potential of TacTID for robotic applications requiring precise contact force and terrain identification in real-time.