煤炭异物分拣是煤炭洗选过程中保障生产安全、提高煤炭质量的关键环节之一。近些年发展起来的多机械臂煤炭异物分拣机器人广泛应用于煤炭洗选过程，代替手选矸环节。在煤炭异物分拣过程中，原煤流中矸石和杂物的类别、时空分布规律不同及皮带速度、过煤量上限差异等因素，都对多机械臂煤炭异物分拣机器人的分拣策略、分拣结果产生影响，如何提高这些复杂因素下的分拣效率和效益是必须解决的关键技术难题之一。因此，本文聚焦输送机带速和过煤量上限差异、原煤流和异物分布波动等复杂环境条件下的多机械臂煤炭异物分拣机器人任务分配方法研究，提高煤炭异物分拣效率、收益和稳定性。

针对煤炭异物种类与特征不同、到达时间与空间位置分布随机导致多机械臂煤炭异物分拣机器人任务分配效率低的难题，深入分析煤炭异物在原煤流中的分布规律，构建基于滚动时间窗的煤炭异物仿真模型。基于现有多机械臂煤炭异物分拣机器人系统，构建相应的运动学模型，并建立带式输送机运动学模型和机械臂轨迹规划模型，为多机械臂煤炭异物分拣机器人任务分配方法研究奠定基础。

针对矸石在时间、空间和特征等维度分布规律受原煤流时变特性影响，导致机器人任务分配结果稳定性差、效率低的问题，研究构建基于M/D/S/∞排队模型的同构多机械臂煤矸分拣任务分配模型。通过机械臂轨迹规划模型的轨迹函数计算机械臂执行任务的时间，基于匹配矩阵与效益矩阵的哈达玛积计算同构多机械臂与矸石队列的环境状态矩阵，采用最小迭代时间的状态转移函数实现环境状态更新。研究基于贪婪自适应权重（Greedy Adaptive Weights, GAW）的任务分配模型优化求解方法，从而提高原煤流时变性影响下煤矸分拣的任务分配效率。

针对铁丝、编织袋、木块等杂物与矸石混杂情况下分拣对象复杂、优先级不同导致的多种类任务分配难题，构建量化煤炭异物分配优先级的效用函数，研究基于效用函数的异构多机械臂煤炭异物分拣任务分配模型，建立综合考虑异构机械臂类型、能力、附加收益等的综合效益函数，以实现分拣矸石总重量和分拣杂物总数量为优化目标。最后，研究基于遗传算法的任务分配模型优化求解方法，提高煤炭异物分拣多评价指标的适应度值。

针对复杂煤炭异物分拣过程中任务分配模型求解时间随任务数量非线性增加，实时性差的问题，研究基于DenseNet网络的动态任务分配方法。构建RGB特征表征煤炭异物在时间、空间和特征等维度的分布规律，描述煤炭异物组成的任务队列。构建面向动态任务分配的不同输送机速度、过煤量上限的多策略任务分配模型数据集，提高数据集的多样性。最后，研究基于DenseNet网络的多策略动态任务分配模型，提高任务分配效率，保证良好的准确率。

设计搭建多机械臂煤炭异物分拣机器人系统实验平台，验证所研究的多机械臂煤炭异物分拣机器人任务分配方法。实验结果表明，煤矸分拣中，GAW的分选率优于FIFO、MF和SPT，具有稳定性。基于遗传算法的组合规则策略在煤炭异物分拣中具有优越性，其最大适应度值相对GAW平均提高14.12%。多策略动态任务分配方法将煤矸分拣任务分配的求解时间降低了84.75%，将煤炭异物分拣任务分配的求解时间降低了92.95%，任务分配结果的准确性良好。工业性试验中，所提出的煤矸分拣任务分配模型整体分选率达到95%以上。

The coal foreign object sorting is one of the key steps in the coal washing process, which is crucial for ensuring production safety and improving coal quality. The multi-manipulator coal foreign object sorting robot developed in recent years is widely used in the coal washing process to replace the hand gangue selection link. In the process of coal foreign object sorting, factors such as the different categories, spatial and temporal distribution rules of gangue and sundry in the raw coal flow, the belt speed and the coal flow upper limit affect the sorting strategy and sorting results of the multi-manipulator coal foreign object sorting robot. How to improve the sorting efficiency and income under these complex factors is one of the key technical problems that must be solved. Therefore, this study focuses on the research on task allocation method of multi-manipulator coal foreign object sorting robot under complex environmental conditions such as the difference of conveyor belt speed and the coal flow upper limit, the fluctuation of raw coal flow and foreign object distribution, so as to improve the efficiency, income and stability of coal foreign object sorting.

Different types and features of coal foreign object, random arrival time and spatial location distribution lead to low task allocation efficiency of multi-manipulator coal foreign object sorting robot. In order to solve the problem, the distribution law of coal foreign object in raw coal flow was deeply analyzed, and a coal foreign object simulation model based on tumbling time window was constructed. Based on the existing multi-manipulator coal foreign object sorting robot system, the corresponding kinematic model is constructed, and the belt conveyor motion model and the manipulator trajectory planning model are established, which lays a foundation for the research on task allocation method of multi-manipulator coal foreign object sorting robot.

Given that the distribution patterns of gangue in terms of time, space and feature are affected by the time-varying of the raw coal flow, resulting in poor stability and low efficiency of the robot task allocation, this study constructs a homogeneous multi-manipulator coal gangue sorting task allocation model based on the M/D/S/∞ queuing model. The time required for the manipulator to perform the task is calculated through the trajectory function of the manipulator trajectory planning model. The environmental state matrix of the isomorphic multi-manipulator and the coal gangue queue is calculated based on the Hadamard product of the matching matrix and the benefit matrix. The environmental state update is achieved by using the minimum iterative time state transition function. This study researches the optimization solution method of task allocation model based on Greedy Adaptive Weights (GAW), so as to improve the efficiency of coal gangue sorting task allocation under the influence of time-varying raw coal flow.

Aiming at the problem of multi-type task allocation caused by complex sorting objects and different priorities in the case of mixed gangue and sundry, such as iron wire, sacks, wood blocks and other sundry objects, a utility function was constructed to quantify the coal foreign object allocation priority, and a heterogeneous multi-manipulator coal foreign object sorting task allocation model based on utility function was studied. A comprehensive benefit function considering the types, capabilities and additional benefits of heterogeneous manipulators is established, and the total mass of the gangue and the total number of the sundry sorted are optimized. Finally, the optimization solution method of task allocation model based on Genetic Algorithm (GA) was studied to improve the fitness value of multi-evaluation indexes in coal foreign object sorting.

Aiming at the problem that the solution time of the task allocation model increases non-linearly with the task number in the process of complex coal foreign object sorting, and the real-time performance is poor, a dynamic task allocation method based on DenseNet network was researched. RGB features were constructed to characterize the distribution of coal foreign object in time, space and feature dimensions, and to describe the task queue composed of coal foreign objects. A multi-strategy task allocation model dataset with different conveyor speeds and coal flow upper limits for dynamic task allocation was constructed to improve the diversity of the dataset. Finally, a multi-strategy dynamic task allocation model based on DenseNet network was studied to improve the efficiency of task allocation, and ensure good accuracy.

A multi-manipulator coal foreign object sorting robot system experimental platform was designed and built to verify the task allocation method of the multi-manipulator coal foreign object sorting robot. Experimental results show that GAW has better sorting rate than First-in-first-out (FIFO), Mass First (MF), and Shortest Processing Time (SPT) in coal gangue sorting, and it has stability. The multi-strategy dynamic task allocation method reduces the task allocation solution time of coal ganging sorting by 84.75%, and reduces the task allocation solution time of coal foreign object sorting by 92.95%, and the obtained task allocation results have good accuracy. In the industrial test, the task allocation method of coal gangue sorting was tested, and the overall sorting rate reached more than 95%.

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