A bionic underwater robot body perception autonomous obstacle avoidance method based on a double-path 1D-CNN

By integrating a flexible sensor array and a dual-path 1D-CNN onto a biomimetic underwater robot, efficient identification and obstacle avoidance control of collision events in complex underwater environments are achieved, solving the problems of response delay and large blind spots in existing technologies and improving the obstacle avoidance capabilities of underwater robots.

CN122131795APending Publication Date: 2026-06-02NINGBO INST OF NORTHWESTERN POLYTECHNICAL UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NINGBO INST OF NORTHWESTERN POLYTECHNICAL UNIV
Filing Date
2026-02-05
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing underwater obstacle avoidance technologies suffer from large blind spots, response delays, and sensitivity to light and water quality in complex aquatic environments. They are unable to achieve highly sensitive, robust recognition and timely response to obstacles at close range, making biomimetic underwater robots prone to structural damage or mission failure.

Method used

A biomimetic underwater robot body perception method based on dual-path 1D-CNN is adopted. The robot collects motion signals of the body structure through a flexible sensor array, extracts features using time-domain and frequency-domain branch networks, and combines feature fusion and collision discrimination layers to predict collision probability and issue obstacle avoidance control commands to adjust the robot's motion posture.

Benefits of technology

It achieves highly sensitive and robust recognition and timely response to collision events in complex underwater environments, reduces false alarms and missed alarms, improves the real-time performance and reliability of obstacle avoidance decisions, and ensures the safe movement of robots.

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Abstract

This invention specifically relates to a biomimetic underwater robot body perception and autonomous obstacle avoidance method based on dual-path 1D-CNN, comprising: measuring the deformation data of the structure during water movement using digital image correlation equipment; deploying multiple flexible sensors in an array in areas of significant deformation to accurately acquire deformation signals; a central control unit monitoring the sensor signals in real time and performing collision detection using a lightweight dual-path 1D-CNN algorithm; when a collision signal is detected, the central control unit automatically issues control commands, which are converted into motor output parameters by a central pattern generator to change the robot's motion posture, enabling autonomous obstacle avoidance. This invention achieves real-time motion monitoring and highly robust, low-latency autonomous obstacle avoidance for biomimetic underwater robots in complex aquatic environments, providing an effective self-protection mechanism and improving its swimming safety and intelligence level.
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