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Obstacle-avoidance trajectory planning method for excavators in confined spaces based on improved RRT* algorithm.

Shengjie Fu1,2, Chang Lin1,2, Zhaoyuan Yao3,4,5

  • 1Fujian Key Laboratory of Green Intelligent Drive and Transmission for Mobile Machinery, Huaqiao University, Xiamen, 361021, China.

Scientific Reports
|January 16, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an enhanced RRT* algorithm for autonomous excavator trajectory planning, improving efficiency and smoothness in complex environments. The new method ensures collision-free, energy-efficient paths for unmanned operations.

Keywords:
Confined spaceImproved RRT* algorithmObstacle-avoidance trajectory planningTrajectory optimizationUnmanned autonomous operation

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Area of Science:

  • Robotics and Automation
  • Construction Engineering
  • Artificial Intelligence

Background:

  • Construction machinery is transitioning to unmanned autonomous operation.
  • Excavators require sophisticated trajectory planning for complex and confined environments.
  • Existing algorithms may lack efficiency and smoothness for autonomous tasks.

Purpose of the Study:

  • To propose an obstacle avoidance trajectory planning scheme for autonomous excavators.
  • To enhance path search efficiency and trajectory quality in restricted conditions.
  • To achieve multi-objective optimization for operation duration and motion smoothness.

Main Methods:

  • Developed a simulation model for excavator mechanisms and environments.
  • Enhanced the RRT* algorithm with environmental parameter-based heuristic search and adaptive goal-biased strategy.
  • Utilized quintic Non-Uniform Rational B-Spline (NURBS) curves for bucket tip trajectory optimization.

Main Results:

  • Reduced path length by 3.65%, iteration count by 64.15%, and computation time by 67.9%.
  • Improved trajectory smoothness by 33.4%.
  • Generated collision-free, smooth, and energy-efficient trajectories.

Conclusions:

  • The enhanced RRT* algorithm significantly improves autonomous excavator performance.
  • The approach ensures high efficiency and mechanical reliability for unmanned operations.
  • This method is effective for autonomous excavator navigation in challenging environments.