The invention discloses a
robot pose positioning method and a
system, and relates to the field of
robot positioning, wherein the method comprises the following steps of: acquiring IMU
odometer data asa local reference
system, acquiring a
pose state vector and a
covariance matrix at the previous time according to the local reference
system, sampling the
pose state vector at the previous time, performing unscented transformation to sampling points, predicting the pose
state vector and the
covariance matrix at the previous time subjected to unscented transformation by using a
system model to obtain a prediction value at the
current time, carrying out filtering treatment to the prediction value at the
current time according to the actual measurement value to obtain the relative pose measurement value at the
current time; after filtering, obtaining the global pose
estimation at the current time according to the relative pose measurement value at the current time through coordinate transformation; and carrying out
robot pose positioning according to the global pose
estimation value at the current time. The unscented
Kalman filter algorithm is combined with IMU
odometer data and actual measurement values collected by
GPS satellites or vision systems to obtain global pose
estimation values, which are robust to complex environments and improve positioning precision.