Traditional lifting operations rely heavily on manual experience, which often leads to high operational risks and limited efficiency. To address these issues, this paper proposes an intelligent lifting system with digital operators, conductors, and supervisors, to improve safety and efficiency through multi-agent collaboration. The system uses a BEVFusion-based perception module to support target detection and collision warning during lifting operations. To handle unforeseen situations, a dynamic local lifting path planning method is designed to ensure safe lifting operations. Rather than proposing a fundamentally new algorithm, this study focuses on integrating perception and planning within a unified intelligent lifting system. The experimental results show that the system can support safe lifting operations under the tested conditions and demonstrate its feasibility in practical scenarios.
Zhou et al. (Mon,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: