Mobile robot positioning method

A mobile robot, positioning method technology, applied in the direction of re-radiation of instruments, electromagnetic waves, utilization of re-radiation, etc., can solve the problems of low accuracy, noise interference, inability to have timeliness, etc., to improve positioning accuracy and accelerate matching speed. Effect

Pending Publication Date: 2020-03-27
HEFEI CSG SMART ROBOT TECH CO LTD
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Problems solved by technology

[0004] However, due to the cumulative error of the odometer and the interference of different noises in the Kalman filter positioning method, the error will increase with time during the positioning process.
The adaptive Monte Carlo positioning requires that although the Kalman filter algorithm is relatively stable, its overall positioning accuracy is not high, and a large number of particles are requ

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Embodiment Construction

[0054] In order to further illustrate the features of the present invention, please refer to the following detailed description and accompanying drawings of the present invention. The accompanying drawings are for reference and description only, and are not intended to limit the protection scope of the present invention.

[0055] Such as figure 1 As shown, this embodiment discloses a mobile robot positioning method, including the following steps S1 to S5:

[0056] S1. Place the robot equipped with two-dimensional laser radar in the current positioning environment, and obtain the map point cloud of obstacles;

[0057] S2. Use the adaptive Monte Carlo positioning algorithm to generate particles that obey the Gaussian distribution near the initial pose of the robot, and update the pose of each particle according to the mixed noise, and estimate the current pose of the robot according to the pose weight of the particles. ;

[0058] S3. Use the current pose of the robot to conve...

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Abstract

The invention discloses a mobile robot positioning method, which belongs to the technical field of mobile robot positioning, and comprises the steps of placing a robot carrying a two-dimensional laserradar in a current positioning environment, and obtaining map point cloud of an obstacle; estimating the current pose of the robot by adopting a self-adaptive Monte Carlo positioning algorithm; converting the real-time data of the two-dimensional laser radar into point cloud PTCloud under the same coordinate system as the map point cloud by using the current pose of the robot; taking each frame of point cloud PTCloudscan as an input of an iterative closest point to obtain a rotation matrix R and a translation matrix T of the current frame of point cloud PTCloudscan relative to the map point cloud; and calculating the final pose of the robot according to the rotation matrix R and the translation matrix T. The pose obtained by adopting the adaptive Monte Carlo positioning algorithm is usedas the reference value to transform the point cloud coordinate system of the two-dimensional laser radar, so that the point cloud coordinate system is close enough to the current map point cloud, thematching speed of the iterative closest point is accelerated, and the positioning precision is improved.

Description

technical field [0001] The invention relates to the technical field of mobile robot positioning, in particular to a mobile robot positioning method. Background technique [0002] With the rapid development of science and technology and the advent of the era of artificial intelligence, mobile robots have developed rapidly and have been widely used in various industries. Among them, how to let the robot know its own position in the current environment and also feedback the position during the movement requires the use of positioning technology. When most robots work, high-precision positioning is first required to perform subsequent tasks. Therefore, how to position the robot in real time, accurately and efficiently becomes the key to the problem. [0003] The existing positioning technology is based on Kalman filtering (KF), which is an algorithm that uses the linear system state equation to optimally estimate the system state through the input and output observation data of...

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Application Information

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IPC IPC(8): G01S17/89G01S17/93G01C21/00
CPCG01S17/89G01S17/93G01C21/005Y02T10/40
Inventor 张永志魏立群章海兵褚衍超许志瑜
Owner HEFEI CSG SMART ROBOT TECH CO LTD
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