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Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making.

Youngbo Shim1, Gon-Woo Kim2

  • 1Mechanical Technology Research Center, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea. shim36145@gmail.com.

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Summary
This summary is machine-generated.

This study introduces a new collision avoidance method for mobile robots using Entry and Bypass modes. This approach enhances stability and efficiency in narrow passages and complex environments.

Keywords:
decision-makinglocal path planningmobile robotmotion planningnavigationobstacle avoidance

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Area of Science:

  • Robotics
  • Artificial Intelligence

Background:

  • Conventional mobile robot obstacle avoidance methods often lead to instability and inefficient paths, particularly in confined spaces.
  • Existing methods may cause undesirable zig-zag motions when navigating around obstacles.

Purpose of the Study:

  • To develop a more stable and efficient collision avoidance method for mobile robots.
  • To address the limitations of conventional methods in narrow passages and complex environments.

Main Methods:

  • Introduction of two distinct obstacle avoidance strategies: Entry mode for navigating gaps and Bypass mode for safe detours.
  • Integration of these modes with the Expanded Guide Circle (EGC) method, incorporating selective decision-making.

Main Results:

  • The proposed method demonstrates improved stability compared to conventional approaches.
  • Efficient navigation through narrow passages and complex environments was validated through simulations and experiments.

Conclusions:

  • The novel Entry and Bypass mode strategy, combined with the Expanded Guide Circle method, provides a robust and efficient solution for mobile robot collision avoidance.
  • The findings confirm the practical applicability and effectiveness of the proposed method in real-world scenarios.