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A multi-robot collaborative target positioning method based on robocup3d

A target positioning, multi-robot technology, applied in the field of multi-robot cooperative target positioning based on RoboCup3D, which can solve the problems of machine performance, susceptibility to visual noise, and large errors.

Active Publication Date: 2019-10-22
宁波知微瑞驰信息科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The positioning results of a single robot are easily affected by visual noise, machine performance, and large errors, and multi-robot collaborative positioning can effectively solve this problem

Method used

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  • A multi-robot collaborative target positioning method based on robocup3d
  • A multi-robot collaborative target positioning method based on robocup3d
  • A multi-robot collaborative target positioning method based on robocup3d

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Embodiment Construction

[0065] A RoboCup3D-based multi-robot collaborative target positioning method of the present invention will be described in detail below with reference to the embodiments and drawings.

[0066] A RoboCup3D-based multi-robot collaborative target positioning method of the present invention uses information fusion methods such as extended Kalman filter and particle filter to effectively fuse the relative observations of the target through multiple robot vision sensors, and then completes the task of collaborative positioning . The present invention utilizes the extended Kalman filtering method to fuse the motion information and the relative observation information cooperative positioning filtering equation, and analyzes its positioning characteristics in detail. The accuracy and effectiveness of the EKF positioning algorithm are verified by simulation experiments. For the multi-robot cooperative localization problem with unknown initial conditions, research and analyze the cooper...

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Abstract

The invention relates to a RoboCup 3D-based multi-robot cooperative target positioning method which comprises the following steps: according to an extended kalman filter algorithm, calculating current global robot position information to forecast global robot positions; according to the extended kalman filter algorithm, establishing a vision observation model, and recursively calculating the global robot positions and a covariance matrix through propagation and updating; and according to a particle filter algorithm, expressing posterior probability by a series of randomly drawn state vector samples, using distribution of a series of drawn samples to represent global robot position distribution, and adopting a resampling method to effectively solve the degeneration problem in sequential importance sampling. According to the RoboCup 3D-based multi-robot cooperative target positioning method, by combining the advantages of the two methods, the calculation time is shortened while the accuracy is improved, and real-time positioning is reached, namely, relative observed quantities of a target object are effectively fused through multiple robot vision sensors, and thus cooperative positioning is finished.

Description

technical field [0001] The invention relates to a football positioning method. In particular, it relates to a RoboCup3D-based multi-robot collaborative target positioning method that uses extended Kalman filter and particle filter to optimize multi-robot positioning. Background technique [0002] At present, in the related technologies of robot positioning, the multi-robot collaborative system can improve the ability and efficiency of robots to complete various advanced tasks through the cooperation between robots in the system. Compared with a single robot, the multi-robot system has shown great advantages in all aspects, and has the advantages of good fault tolerance, high efficiency, good scalability, and strong robustness. [0003] Among the many research problems of multi-robot collaborative systems, the most basic problem is the positioning problem. The positioning ability of robots in the environment is the basis for completing various advanced tasks. Therefore, mul...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/00
Inventor 喻梅胡晓凯王建荣于健高洁徐天一
Owner 宁波知微瑞驰信息科技有限公司