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Global fusion positioning method based on self-adaptive Monte Carlo and feature matching

A technology that integrates positioning and feature matching, and is used in the re-radiation of electromagnetic waves, measuring devices, instruments, etc.

Active Publication Date: 2019-04-26
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] In view of the above-mentioned deficiencies in the prior art, the global fusion positioning method based on adaptive Monte Carlo and feature matching provided by the present invention solves the shortcomings of the existing adaptive Monte Carlo global positioning algorithm

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  • Global fusion positioning method based on self-adaptive Monte Carlo and feature matching
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  • Global fusion positioning method based on self-adaptive Monte Carlo and feature matching

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Embodiment Construction

[0077] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0078] refer to figure 2 , figure 2 A flowchart showing a global fusion positioning method based on adaptive Monte Carlo and feature matching; as figure 2 As shown, the method S includes steps S1 to S14.

[0079] In step S1, the grid map generated by the robot when walking in the detection environment is obtained, and the map line features in the grid map are extracted and stored in the map feature database; step S1 ca...

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Abstract

The invention discloses a global fusion positioning method based on self-adaptive Monte Carlo and feature matching, which comprises the following steps of: extracting map line features in a grid map and storing the map line features in a map feature database; extracting the scan line features of a non-second frame of a laser radar scan map, and initializing the particle set pose of the self-adaptive Monte Carlo by adopting the estimated pose calculated by the first frame of the laser radar scan map; updating the pose and weight of the particles by adopting odometer data, a motion model, a laser radar scan map and a measurement model for a second frame of laser radar scan map; updating the initial pose of a part of particles in a particle set by adopting the estimated pose calculated by thelaser radar scan map for the remaining frames of the laser radar scan map; updating the weight of corresponding particles; and meanwhile, updating the pose and weight of the rest particles in the particle set by adopting the odometer data, the motion model, the laser radar scan map and the measurement model, and finally combining the two particle sets updated with the pose and the weight into a new particle set.

Description

technical field [0001] The invention relates to the technical field of robot positioning, in particular to a global fusion positioning method based on adaptive Monte Carlo and feature matching. Background technique [0002] A mobile robot refers to a device that completes environmental perception, dynamic decision-making and planning, behavior control, and autonomous movement in an unknown environment or a partially unknown environment. For a mobile robot, positioning is to determine the pose (including position and heading angle) of the robot in the environment map. It is not only the basic link for the mobile robot to complete the environment map, but also the key technology for the robot to realize autonomous navigation. [0003] At present, when the robot realizes global positioning, it only estimates its global position in the environment map based on the sensor information. Since there is no prior information of the initial pose, the unimodal distribution cannot be use...

Claims

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Application Information

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IPC IPC(8): G01C21/20G01S17/88
CPCG01C21/20G01S17/88
Inventor 杨帆章洋胡丁文
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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