Distributed multi-robot synergetic location algorithm

Abstract

The invention discloses a distributed multi-robot synergetic location algorithm. The Distributed multi-robot synergetic location algorithm aims at n robots (respectively identified as R1, R2...Rn) which are provided with locating devices and can communicate mutually and steps such as a synergetic location algorithm at time of k=1 and a synergetic location algorithm at time of k+1 (k=1,2...). The method is a distributed bayes estimation algorithm. Under the premise that a decoupling approximation is not carried out on a system model, three-type alignment sensor data such as movement metrical information of the robots, external observation information of a single robot and relative observation information between the robots are fused in robot local; the communication of the robot is point-to-point communication which comprises two parts: one of the parts is the communicated of the relative observation information between two robots which relatively observe, the other of the parts is all robots form a communication chain, and the communication content of adjacent robots is associated state estimation of robots after a sender fuses local alignment sensor data. The method has the advantages of being modularized, good in expandability, good in fault tolerance and the like.

Description

technical field [0001] The invention belongs to a multi-robot positioning algorithm, and relates to a distributed multi-robot cooperative positioning algorithm. Background technique [0002] With the development of science and technology, multi-robot systems (including indoor robots, outdoor robots, unmanned aerial vehicles, underwater vehicles, etc.) are being widely used in scientific research, agriculture, medical care, military and other fields. Robot positioning (that is, determining the position, azimuth, etc.) of the robot is often a basic requirement to ensure the normal operation of the robot. A single robot can measure its own motion information through code discs, inertial measurement units, etc., and can estimate its own state. Positioning errors from this extrapolation method accumulate over time. Robots can suppress the growth of this positioning error through external observations, such as GPS observations, observations of known landmarks, and so on. [000...

AI Technical Summary

Problems solved by technology

The existing distributed computing distributed co-location algorithm has strict requirements on the synchronization between platforms, and often needs to broadcast information between platforms, which directly affects the fault tolerance and scalability of the algorithm.

Images