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Research on path planning of robotic arms based on DAPF-RRT algorithm.

Zhenggang Wang¹, Junyang Tang¹, Fangxu Yi¹

¹School of Electrical Engineering, Anhui Polytechnic University, Wuhu, China.

|May 15, 2025

Summary

This study introduces an improved path planning algorithm for robotic arms, enhancing efficiency and smoothness. The new method significantly reduces path length and planning time compared to existing algorithms.

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Area of Science:

Robotics
Artificial Intelligence
Control Systems

Background:

The RRT-Connect algorithm, widely used for robotic arm path planning, suffers from long search times, random node growth, and jerky path turns.
Existing methods struggle with efficient and smooth trajectory generation for complex robotic tasks.

Purpose of the Study:

To develop an enhanced path planning algorithm for robotic arms that addresses the limitations of RRT-Connect.
To improve path efficiency, reduce planning time, and ensure smoother robotic arm movements.

Main Methods:

A novel algorithm combining dynamic step size and artificial potential field is proposed.
Incorporates a goal-biased strategy to mitigate scattered sampling points.
Employs a dynamic step size strategy for faster expansion.
Integrates artificial potential fields to guide node growth and reduce randomness.
Utilizes cubic B-splines for path pruning and smoothing.

Main Results:

The improved algorithm demonstrated a 15.4% reduction in path length.
Achieved a 49.2% decrease in planning time compared to RRT-Connect.
Resulted in smoother paths with fewer redundant points and turns, reducing robotic arm shaking.

Conclusions:

The proposed algorithm offers a significant improvement over RRT-Connect for robotic arm path planning.
The combination of dynamic step size, artificial potential field, and B-spline smoothing effectively enhances path quality and efficiency.
This approach holds promise for more efficient and precise robotic arm operations.