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Enhancing Target Tracking: A Novel Grid-Based Beetle Antennae Search Algorithm and Confusion-Aware Detection.

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Summary

This study introduces an improved beetle antennae search algorithm and a lightweight multi-target detection system for unmanned aerial vehicles. The enhanced system offers faster, more robust tracking, even with confusing targets and limited resources.

Keywords:
bionic algorithmsobject detectionpath planningtracking controlunmanned aerial vehicle

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Area of Science:

  • Computer Vision
  • Robotics
  • Artificial Intelligence

Background:

  • Unmanned aerial vehicle (UAV) target tracking faces challenges like limited computation, real-time needs, and target confusion.
  • Existing methods struggle with efficiency and robustness in complex tracking scenarios.

Purpose of the Study:

  • To develop an efficient and robust multi-target detection and positioning system for UAVs.
  • To enhance UAV tracking performance under resource constraints and target ambiguity.

Main Methods:

  • Proposed a grid-based beetle antennae search algorithm with secondary search and rollback for improved efficiency.
  • Integrated You Only Look Once (version 8) for detection, with a confusion-aware mechanism using corner detection, feature points, and dictionary matching.
  • Utilized depth information for precise target localization.

Main Results:

  • The grid-based beetle antennae search algorithm demonstrated superior convergence speed and path length compared to mainstream algorithms.
  • The confusion-aware mechanism showed high discriminative ability on a custom interference dataset.
  • The overall system achieved significant speed improvements (over 89% in challenging environments, over 233% vs. previous work) and met real-time requirements.

Conclusions:

  • The proposed grid-based beetle antennae search algorithm and lightweight multi-target detection system significantly enhance UAV tracking performance.
  • The system effectively addresses challenges of limited resources, real-time processing, and target confusion, improving robustness and speed.