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Mobile robot synchronous positioning and map building method

A mobile robot, synchronous positioning technology, applied in instrumentation, 3D modeling, surveying and navigation, etc., can solve the problems of numerical instability and large amount of calculation, and achieve the effect of improving position estimation accuracy and construction accuracy

Pending Publication Date: 2020-03-20
SHANDONG UNIV OF TECH
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Problems solved by technology

However, when the standard CKF is used in SLAM, there are disadvantages such as large amount of calculation and unstable value in the recursive process.
CKF-SLAM algorithm still has room for improvement in terms of accuracy

Method used

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  • Mobile robot synchronous positioning and map building method
  • Mobile robot synchronous positioning and map building method
  • Mobile robot synchronous positioning and map building method

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Embodiment Construction

[0051] The preferred embodiments of the present invention are given below, and are described in conjunction with the accompanying drawings and simulation examples.

[0052] The object of the present invention is achieved through the following steps:

[0053] (1) Establish a system model, including robot motion model, observation model, and environmental feature model; and convert the colored process noise model into a Gaussian white noise model. details as follows:

[0054] I. Constructed robot motion model

[0055]

[0056] where, enter x vx,k ,x vy,k ,x vθ,k is the pose of the robot at time k, x vx,k , x vy,k Indicates the position coordinates of the robot at time k, x vθ,k Indicates the heading of the robot at time k; ΔT is the sampling time of the dead reckoning sensor, V k+1 is the speed of the robot at time k+1, φ k+1 is the rudder angle at time k+1, and B is the wheelbase between the two axes of the robot car. output x vx,k+1 is the pose of the robot at ti...

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Abstract

The invention provides a mobile robot synchronous positioning and map construction method which comprises the following steps: (1) establishment of system models including a robot motion model, an observation model and an environmental characteristic model; conversion of the colored process noise model into a white Gaussian noise model; (2) setting of initial parameters of a mobile robot synchronous positioning and map building algorithm, wherein the initial parameters comprise dead reckoning system parameters and laser radar parameters; (3) state prediction; (4) observing; (5) data association; (6) updating; and (7) state augmentation. The method is characterized by comprising the step (6), in the measurement updating process of standard volume Kalman filtering, an adaptive factor is selected, an autocorrelation covariance matrix and a cross-correlation covariance matrix are adaptively adjusted, the updating process is completed, and meanwhile, the weight ratio between system model prediction information and measurement information can be balanced, so that the positioning precision and the map construction precision are improved.

Description

technical field [0001] The invention relates to a method for synchronous positioning and map construction of a mobile robot, in particular to a method for synchronous positioning and map construction of a mobile robot based on an adaptive volumetric Kalman filter. Background technique [0002] Simultaneous localization and map construction (simultaneous localization and mapping, referred to as: SLAM) means that the mobile robot starts from an unknown position, uses its own sensors to incrementally construct an environmental map during the process of continuous movement, and uses the environment Calculate its own pose based on the position of the target. Simultaneous localization and map construction, first proposed by Smith and Cheeseman in 1988, is used to solve the problem of localization and map construction of mobile robots. Map features are estimated simultaneously. [0003] The current solution to SLAM problems is mainly based on probability estimation. The earliest...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/00G01C21/20G01S17/02G01S17/89G06T17/05
CPCG01C21/005G01C21/20G01S17/89G06T17/05
Inventor 傅桂霞李涛涛邹国锋刘丽娜杜钦君吕传浩李金杰
Owner SHANDONG UNIV OF TECH
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