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

Multi-robot SLAM algorithm based on sub-map feature matching

A multi-robot, feature matching technology, applied in the direction of instruments, two-dimensional position/channel control, non-electric variable control, etc.

Active Publication Date: 2019-08-13
SUZHOU UNIV
View PDF9 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-robot SLAM algorithm based on sub-map feature matching, which is used to solve the problem of modeling large-scale environments or environments with high work efficiency requirements

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
  • Multi-robot SLAM algorithm based on sub-map feature matching
  • Multi-robot SLAM algorithm based on sub-map feature matching
  • Multi-robot SLAM algorithm based on sub-map feature matching

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0047] see figure 1 As shown, a multi-robot SLAM algorithm based on submap feature matching includes the following steps:

[0048] Step 1. Use multiple robots to move in the environment, collect environmental information, and create a submap sequence based on the information.

[0049] In this example, see figure 2 As shown, among the plurality of robots in step 1, the trajectory of one robot overlaps with the trajectory of at least one robot among the remaining robots.

[0050] In this embodiment, lidar sensors are installed on the multiple robots in step 1, and a grid map of the environment is created based on the observation information of the lidar.

[0051] Specifically, multiple robots walk in the environment according to a predetermined trajectory. When the collected laser data reaches the threshold, these laser data are used to create a grid sub-map of the environment. Therefore, each robot can create a sub-map based on its own observation data. sequence of maps.

...

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 multi-robot SLAM (Simultaneous Localization And Mapping) algorithm based on sub-map feature matching. The multi-robot SLAM algorithm comprises the steps of: the step 1, acquiring environment information by adopting a plurality of robots, and creating a sub-map sequence according to the environment information; the step 2, matching sub-maps created by a single robot, and constructing the front end of a single robot SLAM algorithm; the step 3, matching the sub-map sequences created by different robots based on a grid map fusion algorithm of the maximum public subgraph,and storing all the matching results; the step 4, calculating the relative poses among the robots according to the results in the step 3; the step 5, constructing multi-robot closed-loop constraints according to the calculation results in the step 3 and the step 4; the step 6, constructing the front end of the multi-robot SLAM algorithm according to the results in the step 2 and the step 5; the step 7, performing optimization of the rear end of the multi-robot SLAM; and the step 8, creating a global grid map. The multi-robot SLAM algorithm based on sub-map feature matching can solve the problem of modeling a large-scale environment or an environment with high requirement on working efficiency.

Description

technical field [0001] The invention belongs to the field of environment modeling by multiple mobile robots, in particular to a multi-robot SLAM algorithm based on graph optimization, and in particular to a multi-robot SLAM algorithm based on sub-map feature matching. Background technique [0002] Simultaneous localization and mapping (SLAM) refers to a technology in which a mobile robot operates in an unknown environment, observes the surrounding environment according to its own sensors, describes the environment, and realizes its own positioning according to the created map. . Robots with this technology can complete more complex tasks such as navigation, path planning, and exploration in unknown environments. Therefore, SLAM technology is also the key to the real autonomy and intelligence of mobile robots. However, when faced with a large-scale environment such as an airport or a museum, it is impossible to complete the modeling of the environment at one time with the p...

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
CPCG05D1/0257G05D1/0221G05D1/0276
Inventor 孙荣川仇昌成郁树梅陈国栋林睿
Owner SUZHOU UNIV
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