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Fig 1.

Network model and time slot allocation.

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Fig 1 Expand

Fig 2.

Time of flight ranging model.

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Table 1.

UWB data grouping.

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Table 1 Expand

Fig 3.

Snake optimizer algorithm optimization process.

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Fig 4.

The process of updating LSTM hyperparameters with the snake optimizer algorithm.

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Table 2.

SO-LSTM algorithm parameters.

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Table 2 Expand

Fig 5.

Process of UWB location prediction based on LSTM.

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Fig 5 Expand

Fig 6.

Crane experimental platform.

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Fig 6 Expand

Fig 7.

Experimental trajectory of crane hook movement in experiment 1.

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Fig 8.

Visualization of ranging error in experiment 1.

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Fig 9.

SO-LSTM loss value curve.

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Fig 10.

Localization trajectory for experiment 1.

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Table 3.

Statistical analysis of positioning errors for three localization methods in experiment 1.

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Table 3 Expand

Fig 11.

Experiment 1: X-axis positioning estimation error.

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Fig 12.

Experiment 1: Y-axis positioning estimation error.

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Fig 13.

Experiment 1: Z-axis positioning estimation error.

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Table 4.

RMSE for all three axes in experiment 1 with three positioning methods.

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Table 4 Expand

Fig 14.

Experimental trajectory of crane hook movement in experiment 2.

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Fig 14 Expand

Fig 15.

Localization trajectory for experiment 2.

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Table 5.

Statistical analysis of positioning errors for three localization methods in experiment 2.

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Table 5 Expand

Fig 16.

Experiment 2: X-axis positioning estimation error.

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Fig 17.

Experiment 2: Y-axis positioning estimation error.

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Fig 18.

Experiment 2: Z-axis positioning estimation error.

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Table 6.

RMSE for all three axes in experiment 2 with three positioning methods.

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Table 6 Expand

Fig 19.

Analysis of position estimation trajectory errors (a) experiment 1 error histogram (b) experiment 2 error histogram.

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Fig 19 Expand

Table 7.

Percentage improvement in SO-LSTM positioning accuracy.

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Table 7 Expand