The invention discloses a
robot tail end
trajectory planning method based on dynamic
visual feedback, which belongs to the field of industrial robots, and comprises the following steps: firstly, shooting two adjacent images by using a camera carried at the
tail end of a
robot in a moving process, and forming a dynamic stereoscopic vision
system through the movement of a
single camera; the positions of virtual optical axes of the two images are continuously rotated and recovered through a reset method, reset calibration of corresponding epipolar lines is achieved, denoising of the three-dimensional images is achieved by continuously using a
Gaussian filter, a mean filter and a Laplacian filter, detail features are sharpened, a
parallax map is generated through a staged decision matching method, and the three-dimensional image is obtained. And finally, taking
parallax map information as limit-level parameters and taking information such as positions, postures, speeds and accelerations of all joints and the
tail end of the
robot as input to be incorporated into a Faster-R-CNN deep network, accurately determining a candidate
data set through an RPN layer, improving the optimization speed, and rapidly obtaining the
optimal trajectory of the tail end operation of the robot.