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This study introduces an improved bio-inspired algorithm for autonomous underwater vehicle (AUV) navigation, enhancing geomagnetic navigation by overcoming anomalies. The new method ensures reliable AUV guidance in complex environments.

Keywords:
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Area of Science:

  • Robotics
  • Bio-inspired algorithms
  • Geomagnetic navigation

Background:

  • Autonomous Underwater Vehicles (AUVs) rely on navigation systems that can be disrupted by geomagnetic anomalies.
  • Existing bio-inspired navigation methods lack robustness against these environmental disturbances.
  • Geomagnetic anomalies create extreme value regions, leading to AUVs losing their way.

Purpose of the Study:

  • To develop an improved bio-inspired algorithm for AUV geomagnetic navigation.
  • To enable AUVs to escape from anomalous geomagnetic regions.
  • To enhance the reliability and feasibility of AUV navigation in complex environments.

Main Methods:

  • Formulating the AUV navigation problem as an optimization problem.
  • Introducing an environmental monitoring operator to detect geomagnetic anomaly regions.
  • Employing a behavior constraint operator to guide the AUV out of abnormal areas.
  • Utilizing magnetotaxis searching without a priori information.

Main Results:

  • The proposed algorithm effectively overcomes disturbances from geomagnetic anomalies.
  • The approach demonstrates reliability and feasibility in complex underwater environments through simulations.
  • The method successfully guides AUVs out of problematic navigation zones.

Conclusions:

  • The improved bio-inspired algorithm offers a robust solution for AUV geomagnetic navigation.
  • The developed operators enhance AUVs' ability to navigate through challenging geomagnetic conditions.
  • This research contributes to more dependable autonomous underwater exploration.