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Route planning of mobile robot based on improved RRT star and TEB algorithm.

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Summary
This summary is machine-generated.

This study introduces a novel fusion algorithm for mobile robot path planning. The enhanced algorithm significantly reduces path length and turning points, ensuring smooth, obstacle-avoiding trajectories that respect robot kinematics.

Keywords:
AGVKinematicPath planningRRT* algorithmTEB algorithm

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Mobile robot path planning is crucial for autonomous navigation.
  • Traditional algorithms like RRT* can suffer from suboptimal paths and kinematic limitations.
  • Ensuring smooth, efficient, and kinematically feasible trajectories is a key challenge.

Purpose of the Study:

  • To develop and evaluate a fusion algorithm combining an enhanced RRT* for global path generation and an optimized TEB for local trajectory planning.
  • To improve path optimality, reduce length and turning points, and enhance path smoothness.
  • To ensure the generated trajectories adhere to mobile robot kinematic constraints.

Main Methods:

  • An enhanced Rapidly-exploring Random Tree star (RRT*) algorithm featuring adaptive sampling and node bias for accelerated global path generation and reduced local optimality.
  • Path redundancy elimination and turning angle constraints to minimize path length and improve smoothness.
  • Kinematic modeling of the mobile robot and optimization of the Trajectory Encoding Bundle (TEB) algorithm for kinematically feasible local trajectories.

Main Results:

  • The enhanced RRT* algorithm reduced path length by 5.8% and the number of turning points by 62.5% compared to the traditional RRT*.
  • The fusion algorithm successfully generated globally optimal, smooth paths that effectively circumvent obstacles.
  • Local trajectories generated by the fusion algorithm precisely matched the mobile robot's kinematic constraints.

Conclusions:

  • The proposed fusion algorithm offers a superior approach to mobile robot path planning.
  • The enhanced RRT* and optimized TEB integration results in more efficient, smoother, and kinematically compliant robot navigation.
  • This method demonstrates significant improvements over conventional RRT* for complex path planning tasks.