ArticleScientific reports2025
Multitask allocation model of the coal foreign object sorting robot based on optimal capacity and benefit.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Robot technology has important application value in coal mines, non-coal mines, and other fields. However, the existing coal gangue multi-task allocation methods cannot be used for the coal foreign object with multi kinds, complex features, and spatiotemporal randomness, and it is difficult to solve comprehensively improve coal quality, human-machine safety and environmental pollution. Firstly, this paper constructs a multi-task allocation model of coal foreign object sorting robot (CFoSR) based on optimal capacity and benefit. The matching function, optimal capacity function and benefit function were used to calculate the environmental state matrix, and the state transfer function was designed to update the environmental state, which described the multi-task allocation problem of coal foreign object sorting. Then, a multi-evaluation index fitness function was designed that comprehensively considered the total mass of gangue sorting and the total number of sundry sorting. According to the scheduling rules such as first-in-first-out (FIFO), benefit first (BF) and shortest process time (SPT), a combined rule strategy based on genetic algorithm (GACRS) is proposed. Finally, the CFoSR simulation environment was built. The action mechanism of scheduling rules, heterogeneous manipulators, belt speed and coal flow upper limit on the multi-task allocation results of CFoSR is deeply analyzed. The simulation results show that the optimal fitness value of GACRS is 24.73% higher than that of adaptive weights based on greedy algorithm(GAW). The comparison results based on CFoSR experimental platform show that the optimal fitness value of GACRS is 14.02% higher than that of GAW. This paper provides a multi-task allocation model and its solution method for intelligent coal foreign object sorting.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.