计算机科学
地铁列车时刻表
会合
调度(生产过程)
分布式计算
运动规划
启发式
机器人
水下
实时计算
运筹学
控制工程
人工智能
工程类
运营管理
操作系统
航空航天工程
地质学
海洋学
航天器
作者
Maksim Kenzin,Igor Bychkov,Nikolai Maksimkin
摘要
The rapid development of marine robotic technology in recent decades has resulted in significant improvements in the self-sufficiency of autonomous underwater vehicles (AUVs). However, simple scenario-based approaches are no longer sufficient when it comes to ensuring the efficient interaction of multiple autonomous vehicles in complex dynamic missions. The necessity to respond cooperatively to constant changes under severe operating constraints, such as energy or communication limitations, results in the challenge of developing intelligent adaptive approaches for planning and organizing group activities. The current study presents a novel hierarchical approach to the group control system designed for large heterogeneous fleets of AUVs. The high-level core of the approach is rendezvous-based mission planning and is aimed to effectively decompose the mission, ensure regular communication, and schedule AUVs recharging activities. The high-level planning problem is formulated as an original acyclic variation of the inverse shift scheduling problem, which is NP-hard. Since regular schedule adjustments are supposed to be made by the robots themselves right in the course of the mission, a meta-heuristic hybrid evolutionary algorithm is developed to construct feasible sub-optimal solutions in a short time. The high efficiency of the proposed approach is shown through a series of computational experiments.
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