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Event-Based Circular Detection for AUV Docking Based on Spiking Neural Network.

Feihu Zhang¹, Yaohui Zhong¹, Liyuan Chen¹

¹School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, China.

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|January 31, 2022

Summary

This summary is machine-generated.

This study introduces a novel method for detecting circular objects for Autonomous Underwater Vehicle (AUV) docking using a Dynamic Vision Sensor (DVS) and Spiking Neural Network (SNN). The approach enhances accuracy and efficiency in underwater docking by reducing motion blur and data redundancy.

Keywords:

AUV DVS Hough transform P4P SNN docking

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Area of Science:

Robotics
Computer Vision
Artificial Intelligence

Background:

Autonomous Underwater Vehicle (AUV) docking requires precise navigation.
Traditional frame-based vision systems suffer from motion blur and data redundancy in dynamic underwater environments.
Limited on-chip resources in AUVs necessitate efficient processing methods.

Purpose of the Study:

To propose a circular object detection method for AUV docking.
To leverage Dynamic Vision Sensor (DVS) and Spiking Neural Network (SNN) for enhanced underwater docking.
To overcome limitations of frame-based recognition and reduce data redundancy.

Main Methods:

Utilized four coplanar, rectangular-constrained circular light sources as docking landmarks.
Combined asynchronous Hough circle transform with an SNN model for landmark coordinate detection.
Employed a Perspective-4-Point (P4P) algorithm for relative pose calculation and a spatiotemporal filter for noise reduction.

Main Results:

The proposed method effectively detects circular landmarks for AUV docking.
Demonstrated reduced motion blur and data redundancy compared to traditional methods.
Achieved high accuracy and efficiency in both software simulations and experimental pool tests.

Conclusions:

The DVS and SNN-based circular object detection method is highly effective for AUV docking.
The approach offers significant improvements in accuracy and efficiency for underwater navigation and docking tasks.
This method provides a robust solution for real-world AUV docking challenges.