A master-sub algorithm fusion strategy for full-coverage path planning of deep-sea mining vehicle clusters
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In deep-sea mining, effective path planning for vehicle clusters is crucial. Notably, few existing path-planning studies consider pipeline-related factors. This paper presents a master-sub algorithm fusion strategy for the full-coverage path planning of deep-sea mining vehicle clusters in a pipe-lifting system. The master-algorithm uses an improved DDQN algorithm to cover mining areas efficiently and avoid hose entanglement. The sub-algorithm combines a modified inner-spiral algorithm with an A * algorithm for wide-area coverage. Experiments show this strategy achieves 100% coverage in complex environments, prevents hose entanglement, and enables vehicle and hose recovery.
Abstract
In deep-sea mining, effective path planning for vehicle clusters is crucial. Notably, few existing path-planning studies consider pipeline-related factors. This paper presents a master-sub algorithm fusion strategy for the full-coverage path planning of deep-sea mining vehicle clusters in a pipe-lifting system. The master-algorithm uses an improved DDQN algorithm to cover mining areas efficiently and avoid hose entanglement. The sub-algorithm combines a modified inner-spiral algorithm with an A * algorithm for wide-area coverage. Experiments show this strategy achieves 100% coverage in complex environments, prevents hose entanglement, and enables vehicle and hose recovery.