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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
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MD5: db1c61c68080ee52a0a6a64a93b7ae96
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
Comma Separated Values - 1.3 MB -
MD5: 0090251f180a6ac9f3a24dbd5e5a6189
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
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MD5: fcbc68c72ee9f4732cfd971a1a352863
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
Plain Text - 391 B -
MD5: b1f4b1f7e031f50d073d575068a1b62a
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
Plain Text - 119 B -
MD5: fc93cc7a28c4484290dc48cb6a2fafc2
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
Comma Separated Values - 4.5 MB -
MD5: 13bed53184652a120a3d3dac021e7e84
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
Comma Separated Values - 4.5 MB -
MD5: 738463171626fccb0a824f590da1df05
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Jun 16, 2025 -
Identification and Validation Data for Robust Inverse Feedforward with Hybrid Modeling
Comma Separated Values - 4.5 MB -
MD5: 2189dee5e45a170e970dae0818374405
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Jun 6, 2025
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May 28, 2025 - 2023_DFG_RCAL-IMS
Dzubba, Marcel, 2025, "Replication Data for: A Nonlinear Elasticity Model and Feedforward Compensation Method to Increase Positioning Accuracy of Industrial Robots", https://doi.org/10.18419/DARUS-4118, DaRUS, V1, UNF:6:zienI5zq/UH4/+DnUSkN+A== [fileUNF]
Industrial robots are relatively inexpensive, compared to conventional machining tools. However, they suffer in terms of positioning and tracking accuracy. To overcome this issue, laser trackers can be used to calibrate the robot or even for positioning control. The spherically mounted reflector used must always be visible to the laser tracker. The... |