Bridging the gap between theoretic research in distributed and learning-based model predictive control and multi-agent applications.
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MPEG-4 Video - 5.8 MB - MD5: 256136379a930f31986db42fb84b2fa5
This video shows how three omnidirectional mobile robots transport an L-shaped object along a circular path.
MPEG-4 Video - 6.2 MB - MD5: dd5ab9db2a4461711cf42b3d424fc195
In this video, five mobile robots push a +-shaped object along a sinusoidal path.
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.
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.
MPEG-4 Video - 12.8 MB - MD5: 387a274fe1a1bb2247ac59a203371433
Visualization of the zonotopic manipulation space using the experimental data from "Rectangle_N4_square.mp4".
Adobe PDF - 2.2 MB - MD5: faaf50d668131d5792fc18dc263947ba
a short introduction into the training data and its purpose
MATLAB Data - 754.8 KB - MD5: 77f69e59ded4a67acc231c28e451b569
training data set 1
MATLAB Data - 745.8 KB - MD5: 104873a233e7f2a7126c88073fa3aa22
training data set 2
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