Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Particle filtering-based SLAM optimization method

A technology of particle filtering and optimization method, applied in two-dimensional position/channel control, non-electric variable control, instrument and other directions, which can solve the problems of robot noise interference and robot task failure.

Inactive Publication Date: 2019-10-15
STATE GRID SICHUAN ELECTRIC POWER CORP ELECTRIC POWER RES INST +1
View PDF5 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The object of the present invention is to provide a kind of SLAM optimization method based on particle filter, solve the problem that the robot receives noise interference and causes the robot to perform the task failure when performing the task

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Particle filtering-based SLAM optimization method
  • Particle filtering-based SLAM optimization method
  • Particle filtering-based SLAM optimization method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0061] The object of the present invention is to provide a kind of SLAM optimization method based on particle filter, solves the problem that the robot receives noise interference when performing a task and causes the robot to perform a task failure.

[0062] name resolution;

[0063] SLAM (simultaneous localization and mapping), also known as CML (ConcurrentMapping and Localization), real-time robot positioning and map construction, or concurrent mapping and positioning. The problem can be described as: put a robot in an unknown position in an unknown environment, is there a way for the robot to gradually draw a complete map of the environment while moving? corner.

[0064] A particle filter-based SLAM optimization method, at least including the following steps;

[0065] Step 1, establishes probability model to robot, described establishment probability model comprises motion probabilistic modeling, sensor observation model establishment and grid map model establishment;

...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a particle filtering-based SLAM optimization method and relates to robot simultaneous positioning and map construction. The problem of failure task execution of a robot causedby noise interference received by the robot during task execution is solved. The particle filtering-based SLAM optimization method comprises the following steps of 1, defining a variable; 2, buildinga probability model according to the variable, wherein the probability model building comprises motion probability model building, sensor observation model building and grid map model building; and 3,optimizing an SLAM according to the particle filtering and probability model, wherein the step of optimizing the SLAM comprises the steps of automatically determining a position by the robot after the map is updated each time, and the automatic position determination of the robot comprises initialization, sampling, scanning, matching, weight calculation and sampling again. The particle filtering-based SLAM optimization method has the advantages that a true state of a target is obtained, and the failure task execution of the robot caused by noise interference received by the robot during taskexecution is prevented.

Description

technical field [0001] The invention relates to real-time robot positioning and map construction, in particular to a particle filter-based SLAM optimization method. Background technique [0002] For various tasks performed by robots in the prior art, whether it is positioning, mapping, or recognition, the environment and state information they need come from sensors. Ideally, the collection of various information from sensors can represent the specific state of the robot and its environment. However, in actual use, due to the characteristics of the sensor itself or the limitation of the environment, noise exists all the time. When the robot is disturbed by noise when performing tasks, the specific state of the environment where the robot is located is different from the specific state of the actual environment, causing the robot to perform tasks. fail. Contents of the invention [0003] The object of the present invention is to provide a kind of SLAM optimization metho...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0214G05D1/0257
Inventor 常政威陈缨彭倩蒲维彭倍刘静葛森刘海龙陈凌王大兴崔弘刘曦
Owner STATE GRID SICHUAN ELECTRIC POWER CORP ELECTRIC POWER RES INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products