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Bidirectional Jump Point Search Path-Planning Algorithm Based on Electricity-Guided Navigation Behavior of Electric

Hao Gong1,2, Xiangquan Tan1,2,3, Qingwen Wu1,2,3

  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Biomimetics (Basel, Switzerland)
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Summary
This summary is machine-generated.

This study introduces a new path-finding algorithm inspired by electric eels, improving search efficiency. The bidirectional jump point search plus (BJPS+) algorithm offers faster, more optimal path generation for known maps.

Keywords:
electricity guidedgrid mapinflection pointsmap preprocessingpath planningrewiring

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Area of Science:

  • Bio-inspired algorithms
  • Computational intelligence
  • Robotics navigation

Background:

  • Electric eels utilize electric organs for sensing and navigation.
  • Traditional path-finding algorithms like A* face challenges in optimality and efficiency.
  • Optimizing path planning is crucial for autonomous systems.

Purpose of the Study:

  • To develop an efficient path-finding algorithm inspired by electric eel navigation.
  • To enhance the performance of traditional A* algorithms.
  • To address optimality challenges in path planning.

Main Methods:

  • Proposed a bidirectional jump point search plus (BJPS+) algorithm.
  • Incorporated a heuristic strategy based on electric eel navigation.
  • Implemented an improved jump point search and map preprocessing.
  • Utilized a rewiring strategy to reduce path inflection points.

Main Results:

  • The BJPS+ algorithm significantly improves search performance.
  • Demonstrated faster optimal path generation compared to traditional methods.
  • Reduced search time and memory overhead in simulations.

Conclusions:

  • The BJPS+ algorithm effectively utilizes bio-inspired strategies for path planning.
  • Electric eel navigation provides a novel approach to enhance algorithm efficiency.
  • This bio-inspired algorithm offers a promising solution for optimal path generation.