Robot pose estimation method and system based on multi-sensor feature fusion

Abstract

The invention provides a robot pose estimation method based on multi-sensor feature fusion, and the method comprises the steps: obtaining two frames of continuous RGB images captured when a robot moves, and inertial sensor information between the two frames of continuous RGB images; preprocessing the two frames of continuous RGB images, cascading and inputting the two frames of continuous RGB images into a predefined image feature extraction network, outputting to obtain image features, inputting inertial sensor information between the two frames of continuous RGB images into a predefined inertial feature extraction network, and outputting to obtain inertial features; and cascading the obtained image features and inertial features, inputting the cascaded image features and inertial features into a predefined multi-sensor fusion neural network for feature fusion to obtain fused features, and obtaining multi-degree-of-freedom pose estimation of the robot according to the fused features. By implementing the method, the problems of low accuracy of pose estimation by using a single sensor and complex calculation and low efficiency of a traditional multi-sensor fusion algorithm can be solved.

Description

technical field [0001] The present invention relates to the field of robot technology, computer image processing technology and visual and inertial odometer field, in particular to a robot pose estimation method and system based on multi-sensor feature fusion. Background technique [0002] Simultaneous localization and mapping (SLAM) has developed rapidly in recent years, and has received more and more attention and applications in various scenarios such as scientific research, industrial production, and daily life. [0003] As the front end of SLAM, odometry technology can be used to estimate the pose of the robot. Therefore, an excellent odometry technology can provide high-quality initial values ​​for the back-end and global map construction of SLAM, so that the robot can perform various tasks accurately and autonomously in complex unknown environments. Typical odometry solutions mainly utilize vision sensors to recover the robot's motion pose from a series of image stre...

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the embodiments of the present invention is to provide a robot pose estimation method and system based on multi-sensor feature fusion, which can solve the problems of low accuracy of pose estimation using a single sensor and complex calculation and low efficiency of traditional multi-sensor fusion algorithms. question

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