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.