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Mapless Navigation Based on 2D LIDAR in Complex Unknown Environments.

Kai Yan1, Baoli Ma1

  • 1The Seventh Research Division, Beihang University, Beijing 100191, China.

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|October 17, 2020
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Summary
This summary is machine-generated.

This study introduces a new method for robot navigation in unknown areas, successfully avoiding obstacles that trap current systems. The approach uses 2D LIDAR to find environmental gaps, enabling efficient path planning for mobile robots.

Keywords:
2D LIDARTurtlebot2complex environmentslocal path planners

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Area of Science:

  • Robotics and Autonomous Systems
  • Artificial Intelligence
  • Sensor Data Processing

Background:

  • Existing local path planners often fail in complex environments, leading to robots becoming trapped by obstacles.
  • Current methods rely on mapping current sensor data for control, which has limitations in dynamic or unknown settings.

Discussion:

  • The novel approach analyzes 2D LIDAR data to identify environmental gaps, utilizing these as sub-goals for navigation.
  • It generates linear and angular velocities suitable for nonholonomic mobile robots.
  • The method operates without global planners or environment maps, reducing computational load.

Key Insights:

  • The proposed navigation strategy effectively prevents robots from getting stuck in complex, unmapped environments.
  • By focusing on gap detection, the system offers a robust alternative to traditional path planning.

Outlook:

  • This technique's low computational complexity and fast response are ideal for robots with limited processing power, potentially lowering manufacturing costs.
  • Successful simulations and real-world tests on the Turtlebot2 platform validate the approach's effectiveness.