Guangdong University of Technology

Junlang Liang

Xin Chen

Jian Gao

Lanyu Zhang

Yun Chen

Zhuojun Zheng

Yuheng Luo

Yunbo He

The present application provides an image stitching method, apparatus and device based on reinforcement learning and a storage medium. The method includes: acquiring initial calibration parameters, collecting a sample image and position information of a motion platform; setting a negative reward function; acquiring a state set and a negative reward value set according to a randomly generated action set, the initial calibration parameters, the position information of the motion platform and the negative reward function to construct a probability kinematics model; constructing a state value function based on an occurrence probability of the state, and acquiring an optimal action by optimizing the state value function; and acquiring optimized calibration parameters through the optimal action and the initial calibration parameters, and carrying out image stitching on corresponding sample images through the optimized calibration parameters. The application solves the technical problem of low image stitching quality in the prior art.

Image stitching method, apparatus and device based on reinforcement learning and storage medium

An XY macro-micro motion stage and a control method thereof based on end feedback. The XY macro-micro motion stage includes a fine-adjusting assembly, a macro-driving assembly and an XY position detecting device. The macro-driving assembly includes an X-direction macro-driving unit, a Y-direction macro-driving unit, an X-direction mounting plate and a Y-direction mounting plate. The XY position detecting device is configured to obtain its position on the X axis and Y axis.

XY macro-micro motion stage and control method thereof based on end feedback

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Guangzhou, China

Junlang Liang