Introduction - If you have any usage issues, please Google them yourself
In order to improve the adaptability of the quadruped robot in complex environments, the environment percep-
tion strategy based on time of flight (TOF) camera is investigated, and the terrain recognition and path planning algorithms
are improved. Firstly, the Gaussian process regression (GPR) model is used to calibrate the range error of the TOF camera,
and with this model, the high-order computation and complex function composition caused by polynomial or trigonometric
function models are avoided. Based on the depth information of the environment, the terrain is represented with the digi-
tal elevation model (DEM) and recognized by the slope, roughness and step height of the grid. The roughness is obtained
through the dispersion between the slope plane in which the grid locates and its 8-neighbor height points, which avoids the
detection error when using the variance of the terrain height. Based on the terrain information, a path planning algorithm
using sliding window and in