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Related Experiment Video

Updated: May 24, 2026

Operation of the Collaborative Composite Manufacturing (CCM) System

Operation of the Collaborative Composite Manufacturing (CCM) System

Published on: October 1, 2019

Trajectory planning method for pipeline installation robots based on AS-DTRRT.

Zhixiang Liu¹, Wentao Hu², Chunxue Xie³

¹Institute of Mineral Resources, Liaoning Technical University, Fuxin, Liaoning, China.

|May 22, 2026

Summary

This summary is machine-generated.

This study introduces an improved dual-tree RRT algorithm (AS-DTRRT) for pipeline installation robots, enhancing trajectory planning efficiency and safety. The new method reduces runtime and path length, optimizing robotic arm performance in complex mining environments.

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Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole

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Published on: August 26, 2019

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Last Updated: May 24, 2026

Operation of the Collaborative Composite Manufacturing (CCM) System

Operation of the Collaborative Composite Manufacturing (CCM) System

Published on: October 1, 2019

Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole

Visualization of Flow Field Around a Vibrating Pipeline Within an Equilibrium Scour Hole

Published on: August 26, 2019

Area of Science:

Robotics and Automation
Artificial Intelligence
Mechanical Engineering

Background:

Pipeline installation in mine roadways involves robotic arms with complex trajectories influenced by pipeline geometry and dynamic environments.
Existing methods face challenges with long motion trajectories, low efficiency, and collision risks for robotic arms during pipeline installation.

Purpose of the Study:

To develop an improved trajectory planning method for pipeline installation robots to address efficiency and safety concerns.
To enhance the pathfinding capabilities of robotic arms in complex and changeable working environments.

Main Methods:

Proposed an adaptive step-size dynamic environment bias strategy integrated with the dual-tree RRT algorithm (AS-DTRRT).
Incorporated the Artificial Potential Field method for guided node growth and an adaptive step-size strategy to avoid local optima.
Utilized quintic polynomial interpolation for collision-free path trajectory planning, considering joint speed and acceleration constraints.

Main Results:

The AS-DTRRT method demonstrated superior performance compared to RRT*, D-RRT, Bi-RRT*, and A-RRT in simulations and experiments.
Achieved significant reductions in actual runtime (up to 20.22%) and average path lengths (up to 21.17%).
Validated the feasibility of the proposed method for enhancing search efficiency and reducing path lengths in robotic pipeline installation.

Conclusions:

The AS-DTRRT algorithm offers an effective solution for trajectory planning challenges in pipeline installation robots.
The method improves operational efficiency and safety by optimizing robotic arm movements in complex mining environments.