Disclosed is a 
robot positioning and map construction 
system based on 
binocular vision features and IMU information, comprising a binocular information collection, 
feature extraction and matching module, an improved IMU initialization and motion module, a visual SLAM 
algorithm initialization and tracking module, a local mapping module and a loop detection and optimization module. The binocular information collection, 
feature extraction and matching module comprises a binocular ORB 
feature extraction sub-module, a binocular 
feature matching sub-module and an IMU information collection sub-module. The improved IMU initialization and motion module includes an IMU angular rate deviation 
estimation sub-module, a gravity acceleration prediction sub-module, an IMU acceleration deviation 
estimation sub-module and an IMU pre-integration sub-module. The visual SLAM 
algorithm initialization and tracking module includes a tracking inter-frame motion sub-module and a 
key frame generation sub-module. The local mapping module includes a new 
key frame insertion sub-module, a local BA optimization sub-module and a redundant 
key frame elimination sub-module. The loop detection and optimization module includes a loop detection sub-module and a 
global optimization sub-module. The invention provides a 
robot positioning and map construction 
system based on 
binocular vision features and IMU information, which has good robustness, high accuracy and strong adaptability.