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# Control Toolbox
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- ![ Travis (.org) branch] ( https://img.shields.io/travis/ethz-adrl/control-toolbox/3 .0.2.svg?style=popout-square )
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+ ![ Travis (.org) branch] ( https://img.shields.io/travis/ethz-adrl/control-toolbox/v3 .0.2.svg?style=popout-square )
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![ GitHub top language] ( https://img.shields.io/github/languages/top/ethz-adrl/control-toolbox.svg?style=social )
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![ GitHub] ( https://img.shields.io/github/license/ethz-adrl/control-toolbox.svg?style=social )
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@@ -28,12 +28,13 @@ The CT was designed with the following features in mind:
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- intuitive modelling of cost functions and constraints
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- common interfaces for optimal control solvers and nonlinear model predictive control
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- currently supported algorithms:
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- - Single Shooting
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- - iLQR
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- - Gauss-Newton-Multiple-Shooting (GNMS)
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- - Classical Direct Multiple Shooting (DMS)
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- - standardized interfaces for the solvers
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- - IPOPT (first and second order)
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+ - Classical Single Shooting
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+ - iLQR / iLQG (iterative Linear Quadratic Optimal Control)
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+ - Multiple-shooting iLQR
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+ - Gauss-Newton-Multiple-Shooting (GNMS)
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+ - Classical Direct Multiple Shooting (DMS)
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+ - standardized interfaces for the solvers
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+ - IPOPT (first and second order)
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- SNOPT
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- HPIPM
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- custom Riccati-solver
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- solve large scale optimal control problems in MPC fashion.
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- ** Robot Modelling, Rigid Body Kinematics and Dynamics** :
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- - straight-forward interface to a state-of the art rigid body dynamics modelling tool.
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- - implementation of a basic nonlinear-programming-based inverse kinematics solver.
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+ - straight-forward interface to the state-of the art rigid body dynamics modelling tool RobCoGen .
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+ - implementation of a basic nonlinear-programming inverse kinematics solver for fix-base robots .
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- ** Automatic Differentiation** :
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- first- and second order automatic differentiation of arbitrary vector-valued functions including cost functions and constraints
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- - automatic differentiation of rigid body dynamics
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+ - automatic differentiation and code generation of rigid body dynamics
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- derivative code generation for maximum efficiency
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-
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- - ** Simplicity** :
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- - all algorithm flavors and solver backends are available through simple configuration files.
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## Robot Application Examples
@@ -220,7 +217,7 @@ To get started with the control toolbox, please build the repository documentati
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## Acknowledgements
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### Contributors
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- - Markus Giftthaler
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+ - Markus Giftthaler, markusgft (at) gmail (dot) com
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- Michael Neunert
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- Markus Stäuble
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- Farbod Farshidian
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- Ruben Grandia
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- Hamza Merzic
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- ### Project Lead and Maintenance
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+ ### Maintenance
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- Markus Giftthaler, markusgft (at) gmail (dot) com
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- - Michael Neunert, neunertm (at) gmail (dot) com
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+
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### Funding
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This software has been developed at the <a href =" http://www.adrl.ethz.ch " target =" _blank " >Agile & Dexterous Robotics Lab</a >
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