Developing a fast and accurate collision detection strategy for crane-lift path planning in high-rise modular integrated construction

Crane-lift path planning (CLPP) ensures the safe and efficient installation of hefty modules in high-rise modular integrated construction (MiC). The implementation of CLPP requires effective collision detection strategies. However, existing collision detection strategies suffer from limitations in terms of computational intensity or insufficient accuracy. This paper aims to develop a fast and accurate collision detection strategy for CLPP in high-rise MiC projects using a single tower crane, thereby achieving safe and efficient module installation. It is executed with the assumptions that the geometry of the building remains unchanged, the positions and orientations of the lifted module and the tower crane are monitored, and no external loads act on the lifted module. Based on the research scope and assumptions, an octree and bounding box (Oct-Box) integrated strategy is developed. The strategy operates in two stages, the pre-execution and execution stages, supported by two critical technical components: (1) an optimized octree for lifting space division and encoding, and (2) an integrated bounding box algorithm for construction object collision detection. The strategy was evaluated using a real-life MiC project in Hong Kong. The results show that the developed strategy minimized the CLPP time by about 95 %, while ensuring continuous and accurate collision detection. In addition, the strategy was significantly affected by the depth of octree, the encoding method of octree, the bounding box algorithm and the configuration density. The developed Oct-Box strategy for CLPP is novel as it addresses temporal efficiency and spatial tightness in tandem, and marks a breakthrough for collision detection in modular construction.