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

Path planning algorithm for multi-robot team formation in three-dimensional space

A multi-robot, robot technology, applied in two-dimensional position/channel control, instrument, vehicle position/route/altitude control and other directions, can solve the difficulty of accurate formation control of multi-robot systems, and the formation control method cannot be well applied Formation control and high complexity of formation control algorithms

Active Publication Date: 2017-03-15
BEIJING UNIV OF POSTS & TELECOMM
View PDF3 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the formation control method in the three-dimensional space is mainly simplified to the formation problem in the two-dimensional plane, and the complexity of the formation control algorithm in the three-dimensional space is too high, it is difficult to realize the accurate formation control of the multi-robot system
Therefore, the existing formation control methods are not well suited to solve the formation control problem of multi-robots in three-dimensional space
In view of the above problems, a new path planning algorithm based on market auction method and tangent circle method is proposed to solve the problem of formation path planning in multi-robot three-dimensional space

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
  • Path planning algorithm for multi-robot team formation in three-dimensional space
  • Path planning algorithm for multi-robot team formation in three-dimensional space
  • Path planning algorithm for multi-robot team formation in three-dimensional space

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] Define the robot's coordinates and pose with a matrix Indicates that x, y, z represent the position of the robot in the Cartesian coordinate system, θ, Indicates the attitude direction of the robot in the Cartesian coordinate system.

[0042] Take four robots forming a tetrahedron-shaped multi-robot formation shape as an example.

[0043] The initial coordinates are:

[0044] The coordinates of each vertex of the target formation shape are:

[0045] All task assignment methods in the four-robot formation system are shown in Table 1.

[0046] Table 1 All task allocation methods in the four-robot formation system

[0047] k Sumdistance(m) T cost (s)

n 1 44.9762 20.5921 0.8845 2 46.0676 21.4316 0.9133 3 52.5190 21.5433 0.9783 4 51.6614 24.6755 1.0382 5 50.6772 24.6755 1.0286 6 52.6262 21.5433 0.9793 7 46.0676 20.5921 0.8950 8 47.1590 21.4316 0.9239 9 51.6614 20.5921 0.9493 10 5...

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 present invention provides a path planning algorithm for the multi-robot team formation in a three-dimensional space based on the market auction method and the tangent circle method and belongs to the field of intelligent algorithm optimization. According to the invention, the motion simulation for four robots to be in a spatial tetrahedron team formation is realized. The task allocation is conducted based on the market auction method, so that each robot of a multi-robot system can acquire a task coordinate azimuth in the low-energy-consumption and low time-consuming condition. Based on the traditional tangent circle method, a tangent circle method in the three-dimensional space is provided, and the motion path of each robot is planned. Finally, the shape of a team formation is formed, so that all robots are the same in motion posture. The result of simulation studies show that, the above method is short in tem formation time and low in energy consumption, which can realize the path planning task for the multi-robot team formation in the three-dimensional space. The effectiveness and the practicability of the algorithm are verified.

Description

technical field [0001] The invention belongs to the field of intelligent algorithm optimization, and relates to a multi-robot system formation task allocation algorithm based on a market auction method and a multi-robot formation path planning algorithm based on a tangent circle method. Background technique [0002] The formation control method refers to the control method in which the multi-robot system maintains a certain formation and adapts to environmental constraints in the process of reaching the target position. Due to the different tasks and environments of multi-robot formations, researchers have proposed a variety of control methods for robot formations, among which the most commonly used methods are leader-follower-based methods, virtual structure methods, behavior-based methods, and Methods of graph theory and methods of reinforcement learning. [0003] The basic idea of ​​the leader-follower method is that in a multi-robot formation system, there can be one or...

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
IPC IPC(8): G05D1/02
CPCG05D1/0287
Inventor 褚明左权丁宇堃马龙孙汉旭
Owner BEIJING UNIV OF POSTS & TELECOMM
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