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Improving path planning for mobile robots in complex orchard environments: the continuous bidirectional Quick-RRT*

Lei Ye1, Jin Li1, Pu Li1

  • 1School of Intelligent Engineering, Shaoguan University, Shaoguan, China.

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Summary
This summary is machine-generated.

A new Continuous Bidirectional Quick-RRT* (CBQ-RRT*) algorithm improves obstacle avoidance for non-holonomic mobile robots in orchards. This path planning method enhances efficiency and path smoothness, reducing errors in complex environments.

Keywords:
bidirectional expansionmobile robotsorchard environmentspath planningrapidly exploring random tree

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Area of Science:

  • Robotics and Automation
  • Artificial Intelligence
  • Agricultural Engineering

Background:

  • Efficient obstacle-avoidance path planning is crucial for autonomous navigation in complex agricultural environments like orchards.
  • Existing algorithms like unidirectional Quick-RRT* and bidirectional RRT (Bi-RRT) have limitations in path smoothness and efficiency for non-holonomic robots.

Purpose of the Study:

  • To develop an advanced path planning algorithm, Continuous Bidirectional Quick-RRT* (CBQ-RRT*), for efficient and smooth navigation of mobile robots in orchards.
  • To address the zigzagging issue in dual-tree expansion and improve path quality by introducing an optimized expansion cost function and a CreateConnectNode method.

Main Methods:

  • Integration of bidirectional RRT (Bi-RRT) and Quick-RRT* algorithms to create the CBQ-RRT*.
  • Proposal of an expansion cost function evaluating path smoothness and length.
  • Implementation of the CreateConnectNode optimization to resolve path discontinuity at the dual-tree junction.

Main Results:

  • CBQ-RRT* demonstrated superior efficiency compared to unidirectional Quick-RRT* across diverse orchard layouts and terrains.
  • CBQ-RRT* achieved an 8.5% reduction in average path length and a 21.7% decrease in maximum heading angle compared to Bi-RRT*.
  • Field tests showed a significant improvement in path lateral error (0.334 m) compared to Bi-RRT* and Quick-RRT*.

Conclusions:

  • The CBQ-RRT* algorithm effectively overcomes limitations of previous methods, providing smoother and shorter paths for non-holonomic mobile robots.
  • The proposed algorithm shows significant potential for enhancing autonomous navigation systems in complex agricultural settings.
  • CBQ-RRT* offers a robust solution for obstacle-avoidance path planning in challenging orchard environments.