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