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Learning of Causal Observable Functions for Koopman-DFL Lifting
  Linearization of Nonlinear Controlled Systems and Its Application to
  Excavation Automation

Learning of Causal Observable Functions for Koopman-DFL Lifting Linearization of Nonlinear Controlled Systems and Its Application to Excavation Automation

5 April 2021
Nicholas Stearns
S. M. I. H. Harry Asada
ArXivPDFHTML

Papers citing "Learning of Causal Observable Functions for Koopman-DFL Lifting Linearization of Nonlinear Controlled Systems and Its Application to Excavation Automation"

4 / 4 papers shown
Title
Koopman Operators in Robot Learning
Koopman Operators in Robot Learning
Lu Shi
Masih Haseli
Giorgos Mamakoukas
Daniel Bruder
Ian Abraham
Todd D. Murphey
Jorge Cortes
Konstantinos Karydis
AI4CE
25
7
0
08 Aug 2024
On the Utility of Koopman Operator Theory in Learning Dexterous
  Manipulation Skills
On the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills
Yunhai Han
Mandy Xie
Ye Zhao
Harish Ravichandar
32
17
0
23 Mar 2023
Data-Driven Encoding: A New Numerical Method for Computation of the
  Koopman Operator
Data-Driven Encoding: A New Numerical Method for Computation of the Koopman Operator
Jerry Ng
H. Asada
33
4
0
16 Jan 2023
Global, Unified Representation of Heterogenous Robot Dynamics Using
  Composition Operators: A Koopman Direct Encoding Method
Global, Unified Representation of Heterogenous Robot Dynamics Using Composition Operators: A Koopman Direct Encoding Method
Harry Asada
13
9
0
30 Jul 2022
1