Automatic Dual Crane Cooperative Path Planning Based on Multiple RRT Algorithm for Narrow Path Finding Scenario

Abstract

Dual crane lifting, wherein two cranes collaborate to lift a single workpiece, serves as an essential solution in scenarios in which employing a single, sufficiently large crane is impractical due to cost constraints, ground conditions, and spatial limitations. Due to the complexity of double crane lifting operations, the implementation of automated path generation minimizes the risk of human error and removes the potential for accidents by simulating and validating the generated crane path. We propose a novel multiple rapidly-exploring random trees (RRT) based algorithm designed specifically for dual crane systems to produce lifting paths, particularly in challenging ‘narrow path finding’ scenarios. The multiple RRT method is an efficient way to find paths in environments with high complexity and low connectivity through a strategy that allows new trees to be generated and grown whenever a newly generated node that cannot be connected to an existing tree occurs. The proposed path planning algorithm not only adapts the multiple RRT method to the dual crane systems but also incorporates ideas to enhance the optimality of generated paths while reducing computational time. The effectiveness of this algorithm has been validated through a case studies covering various scenario.

Keywords

• Dual crane cooperative system
• path planning
• multiple rapid-exploring random tree