Continuous tracking method suitable for target grabbing of underwater robot

An underwater robot and target technology, applied in the field of visual target tracking, can solve the problems of tracking and grasping failure, and achieve the effect of reliable grasping and stable tracking

Active Publication Date: 2020-05-05
HARBIN ENG UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the current underwater target tracking often causes tracking and grasping failure due to the similarity

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  • Continuous tracking method suitable for target grabbing of underwater robot
  • Continuous tracking method suitable for target grabbing of underwater robot
  • Continuous tracking method suitable for target grabbing of underwater robot

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Embodiment Construction

[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0041] A continuous tracking method suitable for underwater robot target grasping, the main steps include: establishment of nuclear-related motion model, HOG feature extraction, appearance model establishment, model update and iteration. Among them, the establishment of the nuclear correlation motion model requires the KCF method based on correlation filtering to extract a richer training sample set by means of dense sampling. Dense sampling is achieved by cyclic shifting of base samples, generating a sample circulant matrix during sampling.

[0042] Dense sampling is to cyclically shift the region of interest through the characteristics of the circulant matrix to provide training samples for the filter. According to the kernel function theorem, the sample circulation matrix still maintains the circulation property after being mapped...

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Abstract

The invention relates to a continuous tracking method suitable for target grabbing of an underwater robot, and belongs to the technical field of visual target tracking. The method comprises the stepsof establishing a kernel-related motion model; performing HOG feature extraction; establishing an appearance model; and updating and iterating the model. According to the invention, based on the kernel correlation filtering theory, dense sampling is realized through cyclic displacement of base samples, so that a richer training sample set is extracted, HOG features are extracted, the appearance model of a tracking target is established, a kernel function is introduced, so that the nonlinear regression problem is solved, the calculation efficiency is improved, whether reinitialization trackingis needed or not is judged according to a feedback result, a self-discrimination mechanism based on system confidence is provided, and continuous tracking of the target is realized. According to the method, stable tracking of the underwater target can be guaranteed, shielding and mistaken tracking conditions can be automatically judged, so that re-identification and re-tracking are realized, and continuous tracking and reliable grabbing of the underwater target are further completed.

Description

technical field [0001] The invention relates to a continuous tracking method suitable for underwater robot target grasping, belonging to the technical field of visual target tracking. Background technique [0002] For a long time, fishing operations for sea creatures such as sea cucumbers, scallops, and sea urchins have usually been done manually. Limited by objective conditions such as diving time, diving depth, working conditions, fishing costs, and the susceptibility of divers to occupational diseases, the use of underwater robots can reduce fishing costs and improve operational safety. Over the past two decades, the field of computer vision has grown rapidly. Tracking methods range from the earliest mean shift algorithm, subspace algorithm, etc. to sparse representation theory, and then to the current mainstream correlation filtering algorithm and deep learning algorithm. So far, although the target tracking algorithm has made great progress, there are still challenges...

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Application Information

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IPC IPC(8): G06T7/246
CPCG06T7/246G06T2207/20104
Inventor 黄海万兆亮靳佰达吴晗周浩徐明浩姜涛李冀永
Owner HARBIN ENG UNIV
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