贪心策略与调度规则融合的煤矸分拣机器人多任务分配方法
Greedy Strategy and Scheduling Rule Integration for Multi-task Allocation of Coal-gangue Sorting Robots
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摘要: 针对煤炭在生产过程中，复杂的原煤开采工艺与原煤含矸率变化导致选矸皮带机上矸石的到达率、位置坐标和粒度大小非线性变化，严重影响实际工况中煤矸分拣机器人综合收益的问题。本文综合考虑矸石队列特征与排队论调度规则特点，通过结合贪心策略与分别采用不同调度规则的多机械臂任务分配方法，提出了一种时变原煤流下的煤矸分拣机器人多任务分配方法。构建了包含匹配矩阵、效益函数矩阵和环境状态矩阵的多机械臂煤矸分拣机器人多任务分配模型；分析矸石队列各维度信息特点与部分调度规则机理，研究其组合方式，建立部分调度规则组合集；最终通过贪心策略，求解不同时间窗口内不同调度规则的综合收益。分别对瞬时原煤流片段（10m）与长时原煤流片段（500m）进行实验验证，采用顺序抓取方法、调节效益值权重方法与本文方法相对比。实验结果表明，不同的调度规则组合对矸石队列中特征敏感度不同，采用贪心策略自适应选择调度组合规则的方法能够有效减少原煤流时变性所带来的影响，相对于现有方法可以有效提升时变原煤流下煤矸分拣的综合收益。Abstract: This paper addresses the issue that the variation in gangue content of raw coal and the complexity of the production process cause nonlinear changes in the arrival rate, position, and particle size of gangue on the sorting belt, which significantly affects the overall performance of coal-gangue sorting robots in practice. By considering the characteristics of the gangue queue and queueing theory scheduling rules, the paper proposes a multi-task allocation method for coal-gangue sorting robots under time-varying raw coal flow. The method uses a greedy strategy and different scheduling rules for multi-arm robots. A multi-task allocation model is established, including a matching matrix, benefit function matrix, and environmental state matrix. The characteristics of the gangue queue and the mechanisms of certain scheduling rules are analyzed to form a set of rule combinations. Finally, using the greedy strategy, the overall benefit of different scheduling rules in different time windows is optimized. Experiments on short (10m) and long (500m) raw coal flow segments show that different scheduling rule combinations have different sensitivities to gangue queue features. The proposed adaptive scheduling method effectively mitigates the impact of time-varying raw coal flow and outperforms existing methods in improving the overall benefit of coal-gangue sorting.
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