Robot motion estimation method based on dense optical flow

Abstract

The invention relates to a robot motion estimation method based on dense optical flow. The method comprises the steps of calibrating inner parameters and outer parameters of a camera, collecting image sequences and conducting distortion correction, solving the dense optical flow through the polynomial expansion method, purifying light flow, conducting coordinate transformation between image coordinates and robot coordinates, and estimating the motion speed of a robot. The robot motion estimation method based on the dense optical flow solves the problems that in the prior art, motion estimation precision is not high, robustness is poor on the conditions that illumination is uneven and motion is vague, and the function of the camera is restricted. According to the robot motion estimation method based on dense optical flow, the dense optical flow algorithm based on polynomial reduction is introduced, so that the precision of motion estimation is improved. The RANSAC algorithm is applied to the optical flow purification process, so that the robustness of the algorithm is improved. The monocular camera is used, and a lens is arranged downwards in an inclined mode, so that a robot is made to detect the condition ahead in real time, and convenience is brought to completion of tasks such as avoiding barriers and planning paths.

Description

technical field [0001] The invention belongs to the field of robot vision and relates to a method for estimating the moving speed of a robot by using visual information. Background technique [0002] The measurement of motion state is very important in the self-localization, path planning, autonomous navigation and other application fields of mobile robots. In recent years, vision-based methods have become a research hotspot for mobile robot motion estimation. Vision odometry is a method for estimating the relative motion of a robot using a sequence of images captured by a camera. Compared with the traditional robot motion estimation method, the vision-based motion estimation method has the advantages of simple structure and high precision. Moreover, for omnidirectional mobile robots, traditional odometry-based dead reckoning is difficult to achieve, and the advantages of vision-based methods are more obvious. [0003] The patent application No. 201110449925.0 discloses a...

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Problems solved by technology

[0005] Aiming at the problems in the prior art that the motion estimation accuracy is not high, the robustness is poor in the case of uneven illumination and motion blur, and the role of the camera is limited, the present invention provides a robot motion speed estimation based on dense optical flow method, introducing a dense optical flow algorithm based on polynomial decomposition, which improves the accuracy of motion estimation; applying the RANSAC algorithm to the optical flow purification process, which improves the robustness of the algorithm; placing the camera lens obliquely downward, so that the robot can Real-time detection of the situation ahead provides convenience for completing other tasks such as obstacle avoidance and path planning

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