Combined calibration method for multiple sensors of mobile robot

Abstract

The application of the invention discloses a combined calibration method for multiple sensors of a mobile robot. The mobile robot comprises a 2D laser radar and a camera. The method comprises the following steps of: S1, performing internal parameter calibration on the camera by use of a pinhole cameramodel, so as to obtain an internal parameter matrix, which is as shown in the description, of the camera; S2, placing the camera and the 2D laser radar on fixed positions of the mobile robot, and keeping the 2D laser radar and the camera constant in a movement process of the mobile robot; S3, acquiring the position of the camera in a world coordinate system at a moment ti, wherein the position of the camera is as shown in the description, and I is a positive integer; S4, acquiring the position of the 2D laser radar in a world coordinate system at the moment ti, wherein the position of the 2D laser radar is as shown in the description; S5, repeating the S3 and S4 until i is not less than 4; and S6, obtaining a rotation matrix Rcl and a translation matrix tcl of the camera and the 2D laser radar according to an equation as shown in the description. The technical scheme of the application of the invention completely breaks away from the restriction of a calibration target, calibration can be performed under various environments, real-time calibration can be performed in a use process, the problem that positioning error is caused since parameters of existing mobile robots are calibrated only before leaving factory and the parameters fluctuate in the later stage, and users can perform calibration conveniently in the use process.

Description

technical field [0001] The invention relates to a mobile robot, in particular to a multi-sensor joint calibration method of the mobile robot. Background technique [0002] Mobile robot autonomous navigation is a hotspot in the field of robot research. Mobile robot navigation requires the robot to perceive the environment and its own state through sensors, and realize autonomous positioning in an environment with obstacles. Information fusion between different types of sensors is an essential means to improve the robot's environmental understanding and cognitive performance, which provides more accurate environmental information for mobile robots. [0003] In recent years, many systems have begun to integrate the combination of camera and 2DLase-Rangefinder. Vision has the advantages of wide detection range, complete information acquisition, and low price. However, it is easily affected by the external environment such as light, lack of targets, and blurring. question. Lase...

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Problems solved by technology

Then, the calculation of the external parameters is performed by using the estimation results with errors, which makes the accuracy of the calibration results unsatisfactory.

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