Pose estimation method of mobile robot and computer readable storage medium

Abstract

The invention provides a pose estimation method of a mobile robot and a computer readable storage medium. The method comprises the following steps: acquiring multi-source sensor data, the multi-source sensor data comprising: an image acquisition device acquires a ground scene image, an inertial measurement unit acquires ground data, and a wheel encoder acquires ground data; initializing pose estimation of the mobile robot according to scene image detection scene dynamics; collecting ground data by an inertial measurement unit, collecting ground data by a wheel type encoder, and calculating a prior estimator of a state vector of the mobile robot at the current moment and a corresponding covariance transfer matrix through a state transition equation; and iterating the prior estimator of the state vector at the current moment and the corresponding covariance matrix according to the scene image until convergence to complete filtering update. The data acquired by the image acquisition equipment, the data acquired by the inertial measurement unit and the data acquired by the wheel type encoder are used as the input data of the pose estimation and are combined, so that the advantages are complementary, and the tightly coupled pose estimation data can be obtained.

Description

technical field [0001] The present invention relates to the technical field of robot positioning, in particular to a pose estimation method of a mobile robot and a computer-readable storage medium. Background technique [0002] Simultaneous localization and mapping (SLAM) is one of the key technologies for endowing robots with intelligent perception. This technology can obtain the location of the mobile robot itself and a map of its surrounding environment. After decades of research and development, the SLAM problem has integrated theories and research results in multiple fields such as probability estimation, projective geometry, signal processing, and numerical optimization. state estimation problem. The motion equation of SLAM means the position change of the robot from time k-1 to time k. Mathematically it can be expressed as: [0003] x k =f(x k-1 , μ k , ω k ) [0004] Among them, μ k is the sensor reading, ω k for noise. [0005] The observation equation of...

AI Technical Summary

Problems solved by technology

[0010] What is more difficult is that the SLAM problem is a nonlinear problem. In the process of pose estimation, the calculation process is more complicated

[0011] There is a lack of a high-precision pose estimation method in the prior art

Images