Verifiable safety path planning: Utilizing planar analysis for improved lifting operations

Lifting feasibility analysis is crucial for ensuring the safety of lifting operations, especially in multicrane coordinated scenarios. Prior research has delved into shortest paths, smooth trajectories, fuel-efficient routes, and closed-loop control systems. However, the study of open-loop control algorithms focused on optimizing safety-first paths has been conspicuously lacking. Traditional three-dimensional (3D) space-based methods have drawbacks. They consume abundant computational resources, resulting in high-cost and time-consuming computations. Also, the complex 3D-presented results make it arduous for users to evaluate safety margins and optimization potential across diverse working conditions, even with multiple viewpoint changes. This greatly challenges the assessment of existing solutions' reliability and optimization potential, hampering their practical application. This paper presents an innovative planar analysis method for lifting feasibility. By eliminating elevation views and 3D modeling, it substantially cuts down the analysis complexity. Moreover, we introduce the first open-loop control algorithm for finding the safest path. Optimizing within a planar framework, it boosts computational efficiency and enables clear two-dimensional (2D) result visualization. This allows users to quickly identify key conditions without rotating 3D models and easily assess result feasibility and optimality, thus filling a research void. In real-world cases, the safest paths generated by our algorithm outperformed traditional shortest-path methods. The average safety margin increased by 58%, and overall safety risks decreased by 74%. This research fills multiple gaps in the field and shows excellent practicality and safety advantages, especially in high-risk multicrane coordinated lifting operations.