PN 4

SimTech EXC 2075 Project Network 4 "Data-integrated control systems design with guarantees"

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121 to 130 of 346 Results

Rectangle_N4_square.mp4 Jul 25, 2023 - Experiment Videos of a Force-Based Organization and Control Scheme for the Non-Prehensile Cooperative Transportation of Objects MPEG-4 Video - 5.1 MB - MD5: 15251b3389d7ea8b2405068b451bf4f3 Four mobile robots transport an object of rectangular shape along a squared path without rotating it in this video.
T_N5_edge.mp4 Jul 25, 2023 - Experiment Videos of a Force-Based Organization and Control Scheme for the Non-Prehensile Cooperative Transportation of Objects MPEG-4 Video - 8.6 MB - MD5: 258e062176a5fe28497d97fbce7d44e1 Five mobile robots transport a T-shaped object along an edgy path consisting of pure translation and rotation segments.
Visualization_Fig4a.mp4 Jul 25, 2023 - Experiment Videos of a Force-Based Organization and Control Scheme for the Non-Prehensile Cooperative Transportation of Objects MPEG-4 Video - 12.8 MB - MD5: 387a274fe1a1bb2247ac59a203371433 Visualization of the zonotopic manipulation space using the experimental data from "Rectangle_N4_square.mp4".
deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning May 15, 2023 - PN 4-7 Baier, Alexandra; Frank, Daniel, 2023, "deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning", https://doi.org/10.18419/DARUS-3455, DaRUS, V1 deepsysid is a system identification toolkit for multistep prediction using deep learning and hybrid methods. The toolkit is easy to use. After you follow the instructions in the README, you will be able to download a dataset, run hyperparameter optimization and identify your best-performing multistep prediction models with just three commands: dee...
base.py May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning Python Source Code - 8.2 KB - MD5: e68798898b918b6a4ec7154d7866829b
base.py May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning Python Source Code - 5.4 KB - MD5: e0c06d485cd94f590fec94ac13fe1b32
base.py May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning Python Source Code - 983 B - MD5: 180ec7815e9174797f9351f4e0c0bd29
base.py May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning Python Source Code - 1.6 KB - MD5: 6bd280ed8420ae443836a5fc67fd875c
bibo.py May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning Python Source Code - 7.0 KB - MD5: 3ae017576b05d0ae688d86744b53c420
bounded_residual.py May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning Python Source Code - 2.3 KB - MD5: aa2a4e2d35bd8346a4451adbba9b735e

Rectangle_N4_square.mp4

Jul 25, 2023 - Experiment Videos of a Force-Based Organization and Control Scheme for the Non-Prehensile Cooperative Transportation of Objects

MPEG-4 Video - 5.1 MB -

Four mobile robots transport an object of rectangular shape along a squared path without rotating it in this video.

T_N5_edge.mp4

Jul 25, 2023 - Experiment Videos of a Force-Based Organization and Control Scheme for the Non-Prehensile Cooperative Transportation of Objects

MPEG-4 Video - 8.6 MB -

Five mobile robots transport a T-shaped object along an edgy path consisting of pure translation and rotation segments.

Visualization_Fig4a.mp4

Jul 25, 2023 - Experiment Videos of a Force-Based Organization and Control Scheme for the Non-Prehensile Cooperative Transportation of Objects

MPEG-4 Video - 12.8 MB -

Visualization of the zonotopic manipulation space using the experimental data from "Rectangle_N4_square.mp4".

deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

May 15, 2023 - PN 4-7

Baier, Alexandra; Frank, Daniel, 2023, "deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning", https://doi.org/10.18419/DARUS-3455, DaRUS, V1

deepsysid is a system identification toolkit for multistep prediction using deep learning and hybrid methods. The toolkit is easy to use. After you follow the instructions in the README, you will be able to download a dataset, run hyperparameter optimization and identify your best-performing multistep prediction models with just three commands: dee...

base.py

May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

Python Source Code - 8.2 KB -

base.py

May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

Python Source Code - 5.4 KB -

base.py

May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

Python Source Code - 983 B -

base.py

May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

Python Source Code - 1.6 KB -

bibo.py

May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

Python Source Code - 7.0 KB -

bounded_residual.py

May 15, 2023 - deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning

Python Source Code - 2.3 KB -

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