### Repository Summary

 Checkout URI https://github.com/ethz-adrl/ifopt.git VCS Type git VCS Version master Last Updated 2021-01-21 Dev Status MAINTAINED CI status No Continuous Integration Released RELEASED Tags No category tags. Contributing Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

### Packages

Name Version
ifopt 2.0.7

<!-- The actual jenkins documentation job can be found here --> <!-- http://build.ros.org/view/Ldoc/job/Ldoc__ifopt__ubuntu_xenial_amd64/ -->

A modern, light-weight, Eigen-based C++ interface to Nonlinear Programming solvers, such as Ipopt and Snopt.

An example nonlinear optimization problem to solve is defined as:

## Features

Combines the advantages of Ipopt / Snopt and Eigen:

Ipopt / Snopt Eigen
:heavy_check_mark: high-quality solvers for nonlinear optimization :heavy_check_mark: modern, intuitive formulations of vectors and matrices
:x: C++ API inconvenient and error-prone (raw pointers, index management, jacobian construction) :heavy_check_mark: highly efficient implementations
• Solver independent formulation of variables and constraints with Eigen (highly efficient)
• Automatic index management by formulation of variable- and constraint-sets
• Integration: pure cmake find_package(ifopt) or catkin/ROS
• light-weight (~2k lines of code) makes it easy to use and extend

An optimization problem consists of multiple independent variable- and constraint-sets. Each set represents a common concept, e.g. a set of variables might represents spline coefficients, another footstep positions. Similarly, a constraint-set groups similar constraints together. ifopt allows users to define each of these sets independently in separate classes and then builds the overall problem from these sets. (No more worrying adapting indices when adding or removing sets).

find x0, x1                              (variable-sets 0 & 1)
s.t
x0_lower  <= x0 <= x0_upper            (bounds on variable-set x0 \in R^2)

{x0,x1} = arg min c0(x0,x1)+c1(x0,x1)  (cost-terms 0 and 1)

g0_lower < g0(x0,x1) < g0_upper        (constraint-set 0 \in R^2)
g1_lower < g1(x0,x1) < g0_upper        (constraint-set 1 \in R^1)



Supplying derivative information greatly increases solution speed. ifopt allows to define the derivative of each cost-term/constraint-set with respect to each variable-set independently. This ensures that when the order of variable-sets changes in the overall vector, this derivative information is still valid. These "Jacobian blocks" must be supplied through ConstraintSet::FillJacobianBlock() and are then used to build the complete Jacobian for the cost and constraints.

A graphical overview as UML can be seen here.

## Install

The easiest way to install is through the ROS binaries and you're all set!

sudo apt-get install ros-<distro>-ifopt



#### Install dependencies

In case you don't use ROS or the binaries don't exist for your distro, you can easily build these packages from source. For this, install the required dependencies Cmake, Eigen and Ipopt using

sudo apt-get install cmake libeigen3-dev coinor-libipopt-dev



If you want to link to a local installation of Ipopt or to Snopt, see here.

#### Build with cmake

• Install
  git clone https://github.com/ethz-adrl/ifopt.git && cd ifopt
mkdir build && cd build
cmake ..
make
sudo make install # copies files in this folder to /usr/local/*
# sudo xargs rm < install_manifest.txt # in case you want to uninstall the above


• Use: To use in your cmake project, see this minimal CMakeLists.txt:
  find_package(ifopt)
# Formulate (ifopt:ifopt_core) and solve (ifopt::ifopt_ipopt) the problem
# Pull in include directories, libraries, ...



#### Build with catkin

  cd catkin_ws/src
cd ..
catkin_make_isolated # catkin build if you are using catkin command-line tools
source ./devel/setup.bash


  add_compile_options(-std=c++11)
find_package(catkin COMPONENTS ifopt)
include_directories(${catkin_INCLUDE_DIRS}) target_link_libraries(foo${catkin_LIBRARIES})



  <package>
<depend>ifopt</depend>
</package>



## Examples

#### Unit tests & toy problem

Navigate to your build folder in which the Makefile resides, which depends on how you built the code:

cd ifopt/build  # plain cmake
cd catkin_ws/build_isolated/ifopt/devel # catkin_make_isolated
cd catkin_ws/build/ifopt # catkin build



Make sure everything installed correctly by running the test target

make test



You should see ifopt_ipopt-example....Passed (or snopt if installed) as well as ifopt_core-test if gtest is installed.

If you have IPOPT installed and linked correctly, you can also run the binary example directly (again, first navigate to the build folder with the Makefile)

make test ARGS='-R ifopt_ipopt-example -V'



Output:

1.0 0.0



#### towr

A more involved problem, taken from towr, with multiple sets of variables and constraints to generate motions for legged robots produces the following:

## Contribute

We love pull request, whether its interfaces to additional solvers, bug fixes, unit tests or updating the documentation. Please have a look at CONTRIBUTING.md for more information. See here the list of contributors who participated in this project.

## Publications

If you use this work, please consider citing as follows:

@misc{ifopt,
author       = {Alexander W Winkler},
title        = {{Ifopt - A modern, light-weight, Eigen-based C++ interface to
Nonlinear Programming solvers Ipopt and Snopt.}},
year         = 2018,
doi          = {10.5281/zenodo.1135046},
url          = {https://doi.org/10.5281/zenodo.1135046}
}


The research project within which this code was developed: * A. W. Winkler, D. Bellicoso, M. Hutter, J. Buchli, Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization, IEEE Robotics and Automation Letters (RA-L), 2018:

## Authors

Alexander W. Winkler - Initial Work/Maintainer

This was has been carried out at the following institutions:

#### Linking to custom Ipopt or Snopt

If you are building from source and want to use a locally installed version of Ipopt add the path to your Ipopt build folder to your ~/.bashrc, e.g.

export IPOPT_DIR=/home/your_name/Code/Ipopt-3.12.8/build



In case your OS doesn't provide the precompiled binaries or the required version, you can also easily install Ipopt from source as described here. This summary might work for you:

wget https://www.coin-or.org/download/source/Ipopt/Ipopt-3.11.10.zip
unzip Ipopt-3.11.10.zip
cd Ipopt-3.11.10/ThirdParty/Mumps
./get.Mumps  # HSL routines are faster (http://www.hsl.rl.ac.uk/ipopt/)
cd ../../
mkdir build && cd build
../configure --prefix=/usr/local
make
make test
make install
export IPOPT_DIR=pwd



If you need an interface to Snopt, point cmake to that build folder in your ~/.bashrc through e.g.

export SNOPT_DIR=/home/your_name/Code/Snopt



and run cmake as

cmake -DBUILD_SNOPT=ON ..



# Contributing to ifopt

We are grateful to anyone who decides to actively engage in this project. This project and everyone participating in it is governed by the Code of Conduct. By participating, you are expected to uphold this code.

## Question or Issue?

• ROS Answers: If you want to ask a general usage question, please do this at ROS Answers using the tag ifopt. Asking there has the following advantages:

• There are many more people reading questions there so your chances on getting an answer and in a timely manner are much higher.
• In the future other users will search there for similar problems and can find your question and the potential answers.
• Issue tracker: In case you want to report bugs, request features or closely related to the code, the Issue tracker in this repo is the way to go.

## How Can I Contribute?

Unsure where to begin contributing to ifopt? You can start by looking through these beginner and help-wanted issues:

• Good first issues - issues which should only require a few lines of code, and a test or two.
• Help wanted issues - issues which should be a bit more involved than beginner issues.

Further ideas might include: - writing interfaces to additional solvers - reporting bugs - enhance documentation - add unit tests

## Submitting a pull request

Please create a pull request from your forked repo to the master branch.

• Keep pull requests small, focussing on one specific issue.
• Describe concisely what you are solving and reference the corresponding issue.
• Include weblinks to relevant information.
• Include screenshots and animated GIFs in your pull request whenever possible.

We are performing automatic pull request testing, so if you see anything red, please read through the log and update your pull request until the tests pass.

### Repository Summary

 Checkout URI https://github.com/ethz-adrl/ifopt.git VCS Type git VCS Version master Last Updated 2021-01-21 Dev Status MAINTAINED CI status No Continuous Integration Released RELEASED Tags No category tags. Contributing Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

### Packages

Name Version
ifopt 2.0.7

<!-- The actual jenkins documentation job can be found here --> <!-- http://build.ros.org/view/Ldoc/job/Ldoc__ifopt__ubuntu_xenial_amd64/ -->

A modern, light-weight, Eigen-based C++ interface to Nonlinear Programming solvers, such as Ipopt and Snopt.

An example nonlinear optimization problem to solve is defined as:

## Features

Combines the advantages of Ipopt / Snopt and Eigen:

Ipopt / Snopt Eigen
:heavy_check_mark: high-quality solvers for nonlinear optimization :heavy_check_mark: modern, intuitive formulations of vectors and matrices
:x: C++ API inconvenient and error-prone (raw pointers, index management, jacobian construction) :heavy_check_mark: highly efficient implementations
• Solver independent formulation of variables and constraints with Eigen (highly efficient)
• Automatic index management by formulation of variable- and constraint-sets
• Integration: pure cmake find_package(ifopt) or catkin/ROS
• light-weight (~2k lines of code) makes it easy to use and extend

An optimization problem consists of multiple independent variable- and constraint-sets. Each set represents a common concept, e.g. a set of variables might represents spline coefficients, another footstep positions. Similarly, a constraint-set groups similar constraints together. ifopt allows users to define each of these sets independently in separate classes and then builds the overall problem from these sets. (No more worrying adapting indices when adding or removing sets).

find x0, x1                              (variable-sets 0 & 1)
s.t
x0_lower  <= x0 <= x0_upper            (bounds on variable-set x0 \in R^2)

{x0,x1} = arg min c0(x0,x1)+c1(x0,x1)  (cost-terms 0 and 1)

g0_lower < g0(x0,x1) < g0_upper        (constraint-set 0 \in R^2)
g1_lower < g1(x0,x1) < g0_upper        (constraint-set 1 \in R^1)



Supplying derivative information greatly increases solution speed. ifopt allows to define the derivative of each cost-term/constraint-set with respect to each variable-set independently. This ensures that when the order of variable-sets changes in the overall vector, this derivative information is still valid. These "Jacobian blocks" must be supplied through ConstraintSet::FillJacobianBlock() and are then used to build the complete Jacobian for the cost and constraints.

A graphical overview as UML can be seen here.

## Install

The easiest way to install is through the ROS binaries and you're all set!

sudo apt-get install ros-<distro>-ifopt



#### Install dependencies

In case you don't use ROS or the binaries don't exist for your distro, you can easily build these packages from source. For this, install the required dependencies Cmake, Eigen and Ipopt using

sudo apt-get install cmake libeigen3-dev coinor-libipopt-dev



If you want to link to a local installation of Ipopt or to Snopt, see here.

#### Build with cmake

• Install
  git clone https://github.com/ethz-adrl/ifopt.git && cd ifopt
mkdir build && cd build
cmake ..
make
sudo make install # copies files in this folder to /usr/local/*
# sudo xargs rm < install_manifest.txt # in case you want to uninstall the above


• Use: To use in your cmake project, see this minimal CMakeLists.txt:
  find_package(ifopt)
# Formulate (ifopt:ifopt_core) and solve (ifopt::ifopt_ipopt) the problem
# Pull in include directories, libraries, ...



#### Build with catkin

  cd catkin_ws/src
cd ..
catkin_make_isolated # catkin build if you are using catkin command-line tools
source ./devel/setup.bash


  add_compile_options(-std=c++11)
find_package(catkin COMPONENTS ifopt)
include_directories(${catkin_INCLUDE_DIRS}) target_link_libraries(foo${catkin_LIBRARIES})



  <package>
<depend>ifopt</depend>
</package>



## Examples

#### Unit tests & toy problem

Navigate to your build folder in which the Makefile resides, which depends on how you built the code:

cd ifopt/build  # plain cmake
cd catkin_ws/build_isolated/ifopt/devel # catkin_make_isolated
cd catkin_ws/build/ifopt # catkin build



Make sure everything installed correctly by running the test target

make test



You should see ifopt_ipopt-example....Passed (or snopt if installed) as well as ifopt_core-test if gtest is installed.

If you have IPOPT installed and linked correctly, you can also run the binary example directly (again, first navigate to the build folder with the Makefile)

make test ARGS='-R ifopt_ipopt-example -V'



Output:

1.0 0.0



#### towr

A more involved problem, taken from towr, with multiple sets of variables and constraints to generate motions for legged robots produces the following:

## Contribute

We love pull request, whether its interfaces to additional solvers, bug fixes, unit tests or updating the documentation. Please have a look at CONTRIBUTING.md for more information. See here the list of contributors who participated in this project.

## Publications

If you use this work, please consider citing as follows:

@misc{ifopt,
author       = {Alexander W Winkler},
title        = {{Ifopt - A modern, light-weight, Eigen-based C++ interface to
Nonlinear Programming solvers Ipopt and Snopt.}},
year         = 2018,
doi          = {10.5281/zenodo.1135046},
url          = {https://doi.org/10.5281/zenodo.1135046}
}


The research project within which this code was developed: * A. W. Winkler, D. Bellicoso, M. Hutter, J. Buchli, Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization, IEEE Robotics and Automation Letters (RA-L), 2018:

## Authors

Alexander W. Winkler - Initial Work/Maintainer

This was has been carried out at the following institutions:

#### Linking to custom Ipopt or Snopt

If you are building from source and want to use a locally installed version of Ipopt add the path to your Ipopt build folder to your ~/.bashrc, e.g.

export IPOPT_DIR=/home/your_name/Code/Ipopt-3.12.8/build



In case your OS doesn't provide the precompiled binaries or the required version, you can also easily install Ipopt from source as described here. This summary might work for you:

wget https://www.coin-or.org/download/source/Ipopt/Ipopt-3.11.10.zip
unzip Ipopt-3.11.10.zip
cd Ipopt-3.11.10/ThirdParty/Mumps
./get.Mumps  # HSL routines are faster (http://www.hsl.rl.ac.uk/ipopt/)
cd ../../
mkdir build && cd build
../configure --prefix=/usr/local
make
make test
make install
export IPOPT_DIR=pwd



If you need an interface to Snopt, point cmake to that build folder in your ~/.bashrc through e.g.

export SNOPT_DIR=/home/your_name/Code/Snopt



and run cmake as

cmake -DBUILD_SNOPT=ON ..



# Contributing to ifopt

We are grateful to anyone who decides to actively engage in this project. This project and everyone participating in it is governed by the Code of Conduct. By participating, you are expected to uphold this code.

## Question or Issue?

• ROS Answers: If you want to ask a general usage question, please do this at ROS Answers using the tag ifopt. Asking there has the following advantages:

• There are many more people reading questions there so your chances on getting an answer and in a timely manner are much higher.
• In the future other users will search there for similar problems and can find your question and the potential answers.
• Issue tracker: In case you want to report bugs, request features or closely related to the code, the Issue tracker in this repo is the way to go.

## How Can I Contribute?

Unsure where to begin contributing to ifopt? You can start by looking through these beginner and help-wanted issues:

• Good first issues - issues which should only require a few lines of code, and a test or two.
• Help wanted issues - issues which should be a bit more involved than beginner issues.

Further ideas might include: - writing interfaces to additional solvers - reporting bugs - enhance documentation - add unit tests

## Submitting a pull request

Please create a pull request from your forked repo to the master branch.

• Keep pull requests small, focussing on one specific issue.
• Describe concisely what you are solving and reference the corresponding issue.
• Include weblinks to relevant information.
• Include screenshots and animated GIFs in your pull request whenever possible.

We are performing automatic pull request testing, so if you see anything red, please read through the log and update your pull request until the tests pass.

### Repository Summary

 Checkout URI https://github.com/ethz-adrl/ifopt.git VCS Type git VCS Version master Last Updated 2021-01-21 Dev Status MAINTAINED CI status No Continuous Integration Released RELEASED Tags No category tags. Contributing Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

### Packages

Name Version
ifopt 2.0.7

<!-- The actual jenkins documentation job can be found here --> <!-- http://build.ros.org/view/Ldoc/job/Ldoc__ifopt__ubuntu_xenial_amd64/ -->

A modern, light-weight, Eigen-based C++ interface to Nonlinear Programming solvers, such as Ipopt and Snopt.

An example nonlinear optimization problem to solve is defined as:

## Features

Combines the advantages of Ipopt / Snopt and Eigen:

Ipopt / Snopt Eigen
:heavy_check_mark: high-quality solvers for nonlinear optimization :heavy_check_mark: modern, intuitive formulations of vectors and matrices
:x: C++ API inconvenient and error-prone (raw pointers, index management, jacobian construction) :heavy_check_mark: highly efficient implementations
• Solver independent formulation of variables and constraints with Eigen (highly efficient)
• Automatic index management by formulation of variable- and constraint-sets
• Integration: pure cmake find_package(ifopt) or catkin/ROS
• light-weight (~2k lines of code) makes it easy to use and extend

An optimization problem consists of multiple independent variable- and constraint-sets. Each set represents a common concept, e.g. a set of variables might represents spline coefficients, another footstep positions. Similarly, a constraint-set groups similar constraints together. ifopt allows users to define each of these sets independently in separate classes and then builds the overall problem from these sets. (No more worrying adapting indices when adding or removing sets).

find x0, x1                              (variable-sets 0 & 1)
s.t
x0_lower  <= x0 <= x0_upper            (bounds on variable-set x0 \in R^2)

{x0,x1} = arg min c0(x0,x1)+c1(x0,x1)  (cost-terms 0 and 1)

g0_lower < g0(x0,x1) < g0_upper        (constraint-set 0 \in R^2)
g1_lower < g1(x0,x1) < g0_upper        (constraint-set 1 \in R^1)



Supplying derivative information greatly increases solution speed. ifopt allows to define the derivative of each cost-term/constraint-set with respect to each variable-set independently. This ensures that when the order of variable-sets changes in the overall vector, this derivative information is still valid. These "Jacobian blocks" must be supplied through ConstraintSet::FillJacobianBlock() and are then used to build the complete Jacobian for the cost and constraints.

A graphical overview as UML can be seen here.

## Install

The easiest way to install is through the ROS binaries and you're all set!

sudo apt-get install ros-<distro>-ifopt



#### Install dependencies

In case you don't use ROS or the binaries don't exist for your distro, you can easily build these packages from source. For this, install the required dependencies Cmake, Eigen and Ipopt using

sudo apt-get install cmake libeigen3-dev coinor-libipopt-dev



If you want to link to a local installation of Ipopt or to Snopt, see here.

#### Build with cmake

• Install
  git clone https://github.com/ethz-adrl/ifopt.git && cd ifopt
mkdir build && cd build
cmake ..
make
sudo make install # copies files in this folder to /usr/local/*
# sudo xargs rm < install_manifest.txt # in case you want to uninstall the above


• Use: To use in your cmake project, see this minimal CMakeLists.txt:
  find_package(ifopt)
# Formulate (ifopt:ifopt_core) and solve (ifopt::ifopt_ipopt) the problem
# Pull in include directories, libraries, ...



#### Build with catkin

  cd catkin_ws/src
cd ..
catkin_make_isolated # catkin build if you are using catkin command-line tools
source ./devel/setup.bash


  add_compile_options(-std=c++11)
find_package(catkin COMPONENTS ifopt)
include_directories(${catkin_INCLUDE_DIRS}) target_link_libraries(foo${catkin_LIBRARIES})



  <package>
<depend>ifopt</depend>
</package>



## Examples

#### Unit tests & toy problem

Navigate to your build folder in which the Makefile resides, which depends on how you built the code:

cd ifopt/build  # plain cmake
cd catkin_ws/build_isolated/ifopt/devel # catkin_make_isolated
cd catkin_ws/build/ifopt # catkin build



Make sure everything installed correctly by running the test target

make test



You should see ifopt_ipopt-example....Passed (or snopt if installed) as well as ifopt_core-test if gtest is installed.

If you have IPOPT installed and linked correctly, you can also run the binary example directly (again, first navigate to the build folder with the Makefile)

make test ARGS='-R ifopt_ipopt-example -V'



Output:

1.0 0.0



#### towr

A more involved problem, taken from towr, with multiple sets of variables and constraints to generate motions for legged robots produces the following:

## Contribute

We love pull request, whether its interfaces to additional solvers, bug fixes, unit tests or updating the documentation. Please have a look at CONTRIBUTING.md for more information. See here the list of contributors who participated in this project.

## Publications

If you use this work, please consider citing as follows:

@misc{ifopt,
author       = {Alexander W Winkler},
title        = {{Ifopt - A modern, light-weight, Eigen-based C++ interface to
Nonlinear Programming solvers Ipopt and Snopt.}},
year         = 2018,
doi          = {10.5281/zenodo.1135046},
url          = {https://doi.org/10.5281/zenodo.1135046}
}


The research project within which this code was developed: * A. W. Winkler, D. Bellicoso, M. Hutter, J. Buchli, Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization, IEEE Robotics and Automation Letters (RA-L), 2018:

## Authors

Alexander W. Winkler - Initial Work/Maintainer

This was has been carried out at the following institutions:

#### Linking to custom Ipopt or Snopt

If you are building from source and want to use a locally installed version of Ipopt add the path to your Ipopt build folder to your ~/.bashrc, e.g.

export IPOPT_DIR=/home/your_name/Code/Ipopt-3.12.8/build



In case your OS doesn't provide the precompiled binaries or the required version, you can also easily install Ipopt from source as described here. This summary might work for you:

wget https://www.coin-or.org/download/source/Ipopt/Ipopt-3.11.10.zip
unzip Ipopt-3.11.10.zip
cd Ipopt-3.11.10/ThirdParty/Mumps
./get.Mumps  # HSL routines are faster (http://www.hsl.rl.ac.uk/ipopt/)
cd ../../
mkdir build && cd build
../configure --prefix=/usr/local
make
make test
make install
export IPOPT_DIR=pwd



If you need an interface to Snopt, point cmake to that build folder in your ~/.bashrc through e.g.

export SNOPT_DIR=/home/your_name/Code/Snopt



and run cmake as

cmake -DBUILD_SNOPT=ON ..



# Contributing to ifopt

We are grateful to anyone who decides to actively engage in this project. This project and everyone participating in it is governed by the Code of Conduct. By participating, you are expected to uphold this code.

## Question or Issue?

• ROS Answers: If you want to ask a general usage question, please do this at ROS Answers using the tag ifopt. Asking there has the following advantages:

• There are many more people reading questions there so your chances on getting an answer and in a timely manner are much higher.
• In the future other users will search there for similar problems and can find your question and the potential answers.
• Issue tracker: In case you want to report bugs, request features or closely related to the code, the Issue tracker in this repo is the way to go.

## How Can I Contribute?

Unsure where to begin contributing to ifopt? You can start by looking through these beginner and help-wanted issues:

• Good first issues - issues which should only require a few lines of code, and a test or two.
• Help wanted issues - issues which should be a bit more involved than beginner issues.

Further ideas might include: - writing interfaces to additional solvers - reporting bugs - enhance documentation - add unit tests

## Submitting a pull request

Please create a pull request from your forked repo to the master branch.

• Keep pull requests small, focussing on one specific issue.
• Describe concisely what you are solving and reference the corresponding issue.
• Include weblinks to relevant information.
• Include screenshots and animated GIFs in your pull request whenever possible.

We are performing automatic pull request testing, so if you see anything red, please read through the log and update your pull request until the tests pass.

### Repository Summary

 Checkout URI https://github.com/ethz-adrl/ifopt.git VCS Type git VCS Version master Last Updated 2021-01-21 Dev Status MAINTAINED CI status No Continuous Integration Released RELEASED Tags No category tags. Contributing Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

### Packages

Name Version
ifopt 2.0.7

<!-- The actual jenkins documentation job can be found here --> <!-- http://build.ros.org/view/Ldoc/job/Ldoc__ifopt__ubuntu_xenial_amd64/ -->

A modern, light-weight, Eigen-based C++ interface to Nonlinear Programming solvers, such as Ipopt and Snopt.

An example nonlinear optimization problem to solve is defined as:

## Features

Combines the advantages of Ipopt / Snopt and Eigen:

Ipopt / Snopt Eigen
:heavy_check_mark: high-quality solvers for nonlinear optimization :heavy_check_mark: modern, intuitive formulations of vectors and matrices
:x: C++ API inconvenient and error-prone (raw pointers, index management, jacobian construction) :heavy_check_mark: highly efficient implementations
• Solver independent formulation of variables and constraints with Eigen (highly efficient)
• Automatic index management by formulation of variable- and constraint-sets
• Integration: pure cmake find_package(ifopt) or catkin/ROS
• light-weight (~2k lines of code) makes it easy to use and extend

An optimization problem consists of multiple independent variable- and constraint-sets. Each set represents a common concept, e.g. a set of variables might represents spline coefficients, another footstep positions. Similarly, a constraint-set groups similar constraints together. ifopt allows users to define each of these sets independently in separate classes and then builds the overall problem from these sets. (No more worrying adapting indices when adding or removing sets).

find x0, x1                              (variable-sets 0 & 1)
s.t
x0_lower  <= x0 <= x0_upper            (bounds on variable-set x0 \in R^2)

{x0,x1} = arg min c0(x0,x1)+c1(x0,x1)  (cost-terms 0 and 1)

g0_lower < g0(x0,x1) < g0_upper        (constraint-set 0 \in R^2)
g1_lower < g1(x0,x1) < g0_upper        (constraint-set 1 \in R^1)



Supplying derivative information greatly increases solution speed. ifopt allows to define the derivative of each cost-term/constraint-set with respect to each variable-set independently. This ensures that when the order of variable-sets changes in the overall vector, this derivative information is still valid. These "Jacobian blocks" must be supplied through ConstraintSet::FillJacobianBlock() and are then used to build the complete Jacobian for the cost and constraints.

A graphical overview as UML can be seen here.

## Install

The easiest way to install is through the ROS binaries and you're all set!

sudo apt-get install ros-<distro>-ifopt



#### Install dependencies

In case you don't use ROS or the binaries don't exist for your distro, you can easily build these packages from source. For this, install the required dependencies Cmake, Eigen and Ipopt using

sudo apt-get install cmake libeigen3-dev coinor-libipopt-dev



If you want to link to a local installation of Ipopt or to Snopt, see here.

#### Build with cmake

• Install
  git clone https://github.com/ethz-adrl/ifopt.git && cd ifopt
mkdir build && cd build
cmake ..
make
sudo make install # copies files in this folder to /usr/local/*
# sudo xargs rm < install_manifest.txt # in case you want to uninstall the above


• Use: To use in your cmake project, see this minimal CMakeLists.txt:
  find_package(ifopt)
# Formulate (ifopt:ifopt_core) and solve (ifopt::ifopt_ipopt) the problem
# Pull in include directories, libraries, ...



#### Build with catkin

  cd catkin_ws/src
cd ..
catkin_make_isolated # catkin build if you are using catkin command-line tools
source ./devel/setup.bash


  add_compile_options(-std=c++11)
find_package(catkin COMPONENTS ifopt)
include_directories(${catkin_INCLUDE_DIRS}) target_link_libraries(foo${catkin_LIBRARIES})



  <package>
<depend>ifopt</depend>
</package>



## Examples

#### Unit tests & toy problem

Navigate to your build folder in which the Makefile resides, which depends on how you built the code:

cd ifopt/build  # plain cmake
cd catkin_ws/build_isolated/ifopt/devel # catkin_make_isolated
cd catkin_ws/build/ifopt # catkin build



Make sure everything installed correctly by running the test target

make test



You should see ifopt_ipopt-example....Passed (or snopt if installed) as well as ifopt_core-test if gtest is installed.

If you have IPOPT installed and linked correctly, you can also run the binary example directly (again, first navigate to the build folder with the Makefile)

make test ARGS='-R ifopt_ipopt-example -V'



Output:

1.0 0.0



#### towr

A more involved problem, taken from towr, with multiple sets of variables and constraints to generate motions for legged robots produces the following:

## Contribute

We love pull request, whether its interfaces to additional solvers, bug fixes, unit tests or updating the documentation. Please have a look at CONTRIBUTING.md for more information. See here the list of contributors who participated in this project.

## Publications

If you use this work, please consider citing as follows:

@misc{ifopt,
author       = {Alexander W Winkler},
title        = {{Ifopt - A modern, light-weight, Eigen-based C++ interface to
Nonlinear Programming solvers Ipopt and Snopt.}},
year         = 2018,
doi          = {10.5281/zenodo.1135046},
url          = {https://doi.org/10.5281/zenodo.1135046}
}


The research project within which this code was developed: * A. W. Winkler, D. Bellicoso, M. Hutter, J. Buchli, Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization, IEEE Robotics and Automation Letters (RA-L), 2018:

## Authors

Alexander W. Winkler - Initial Work/Maintainer

This was has been carried out at the following institutions:

#### Linking to custom Ipopt or Snopt

If you are building from source and want to use a locally installed version of Ipopt add the path to your Ipopt build folder to your ~/.bashrc, e.g.

export IPOPT_DIR=/home/your_name/Code/Ipopt-3.12.8/build



In case your OS doesn't provide the precompiled binaries or the required version, you can also easily install Ipopt from source as described here. This summary might work for you:

wget https://www.coin-or.org/download/source/Ipopt/Ipopt-3.11.10.zip
unzip Ipopt-3.11.10.zip
cd Ipopt-3.11.10/ThirdParty/Mumps
./get.Mumps  # HSL routines are faster (http://www.hsl.rl.ac.uk/ipopt/)
cd ../../
mkdir build && cd build
../configure --prefix=/usr/local
make
make test
make install
export IPOPT_DIR=pwd



If you need an interface to Snopt, point cmake to that build folder in your ~/.bashrc through e.g.

export SNOPT_DIR=/home/your_name/Code/Snopt



and run cmake as

cmake -DBUILD_SNOPT=ON ..



# Contributing to ifopt

We are grateful to anyone who decides to actively engage in this project. This project and everyone participating in it is governed by the Code of Conduct. By participating, you are expected to uphold this code.

## Question or Issue?

• ROS Answers: If you want to ask a general usage question, please do this at ROS Answers using the tag ifopt. Asking there has the following advantages:

• There are many more people reading questions there so your chances on getting an answer and in a timely manner are much higher.
• In the future other users will search there for similar problems and can find your question and the potential answers.
• Issue tracker: In case you want to report bugs, request features or closely related to the code, the Issue tracker in this repo is the way to go.

## How Can I Contribute?

Unsure where to begin contributing to ifopt? You can start by looking through these beginner and help-wanted issues:

• Good first issues - issues which should only require a few lines of code, and a test or two.
• Help wanted issues - issues which should be a bit more involved than beginner issues.

Further ideas might include: - writing interfaces to additional solvers - reporting bugs - enhance documentation - add unit tests

## Submitting a pull request

Please create a pull request from your forked repo to the master branch.

• Keep pull requests small, focussing on one specific issue.
• Describe concisely what you are solving and reference the corresponding issue.
• Include weblinks to relevant information.
• Include screenshots and animated GIFs in your pull request whenever possible.

We are performing automatic pull request testing, so if you see anything red, please read through the log and update your pull request until the tests pass.

### Repository Summary

 Checkout URI https://github.com/ethz-adrl/ifopt.git VCS Type git VCS Version master Last Updated 2021-01-21 Dev Status MAINTAINED CI status No Continuous Integration Released UNRELEASED Tags No category tags. Contributing Help Wanted (0) Good First Issues (0) Pull Requests to Review (0)

### Packages

Name Version
ifopt 2.0.7

<!-- The actual jenkins documentation job can be found here --> <!-- http://build.ros.org/view/Ldoc/job/Ldoc__ifopt__ubuntu_xenial_amd64/ -->

A modern, light-weight, Eigen-based C++ interface to Nonlinear Programming solvers, such as Ipopt and Snopt.

An example nonlinear optimization problem to solve is defined as:

## Features

Combines the advantages of Ipopt / Snopt and Eigen:

Ipopt / Snopt Eigen
:heavy_check_mark: high-quality solvers for nonlinear optimization :heavy_check_mark: modern, intuitive formulations of vectors and matrices
:x: C++ API inconvenient and error-prone (raw pointers, index management, jacobian construction) :heavy_check_mark: highly efficient implementations
• Solver independent formulation of variables and constraints with Eigen (highly efficient)
• Automatic index management by formulation of variable- and constraint-sets
• Integration: pure cmake find_package(ifopt) or catkin/ROS
• light-weight (~2k lines of code) makes it easy to use and extend

An optimization problem consists of multiple independent variable- and constraint-sets. Each set represents a common concept, e.g. a set of variables might represents spline coefficients, another footstep positions. Similarly, a constraint-set groups similar constraints together. ifopt allows users to define each of these sets independently in separate classes and then builds the overall problem from these sets. (No more worrying adapting indices when adding or removing sets).

find x0, x1                              (variable-sets 0 & 1)
s.t
x0_lower  <= x0 <= x0_upper            (bounds on variable-set x0 \in R^2)

{x0,x1} = arg min c0(x0,x1)+c1(x0,x1)  (cost-terms 0 and 1)

g0_lower < g0(x0,x1) < g0_upper        (constraint-set 0 \in R^2)
g1_lower < g1(x0,x1) < g0_upper        (constraint-set 1 \in R^1)



Supplying derivative information greatly increases solution speed. ifopt allows to define the derivative of each cost-term/constraint-set with respect to each variable-set independently. This ensures that when the order of variable-sets changes in the overall vector, this derivative information is still valid. These "Jacobian blocks" must be supplied through ConstraintSet::FillJacobianBlock() and are then used to build the complete Jacobian for the cost and constraints.

A graphical overview as UML can be seen here.

## Install

The easiest way to install is through the ROS binaries and you're all set!

sudo apt-get install ros-<distro>-ifopt



#### Install dependencies

In case you don't use ROS or the binaries don't exist for your distro, you can easily build these packages from source. For this, install the required dependencies Cmake, Eigen and Ipopt using

sudo apt-get install cmake libeigen3-dev coinor-libipopt-dev



If you want to link to a local installation of Ipopt or to Snopt, see here.

#### Build with cmake

• Install
  git clone https://github.com/ethz-adrl/ifopt.git && cd ifopt
mkdir build && cd build
cmake ..
make
sudo make install # copies files in this folder to /usr/local/*
# sudo xargs rm < install_manifest.txt # in case you want to uninstall the above


• Use: To use in your cmake project, see this minimal CMakeLists.txt:
  find_package(ifopt)
# Formulate (ifopt:ifopt_core) and solve (ifopt::ifopt_ipopt) the problem
# Pull in include directories, libraries, ...



#### Build with catkin

  cd catkin_ws/src
cd ..
catkin_make_isolated # catkin build if you are using catkin command-line tools
source ./devel/setup.bash


  add_compile_options(-std=c++11)
find_package(catkin COMPONENTS ifopt)
include_directories(${catkin_INCLUDE_DIRS}) target_link_libraries(foo${catkin_LIBRARIES})



  <package>
<depend>ifopt</depend>
</package>



## Examples

#### Unit tests & toy problem

Navigate to your build folder in which the Makefile resides, which depends on how you built the code:

cd ifopt/build  # plain cmake
cd catkin_ws/build_isolated/ifopt/devel # catkin_make_isolated
cd catkin_ws/build/ifopt # catkin build



Make sure everything installed correctly by running the test target

make test



You should see ifopt_ipopt-example....Passed (or snopt if installed) as well as ifopt_core-test if gtest is installed.

If you have IPOPT installed and linked correctly, you can also run the binary example directly (again, first navigate to the build folder with the Makefile)

make test ARGS='-R ifopt_ipopt-example -V'



Output:

1.0 0.0



#### towr

A more involved problem, taken from towr, with multiple sets of variables and constraints to generate motions for legged robots produces the following:

## Contribute

We love pull request, whether its interfaces to additional solvers, bug fixes, unit tests or updating the documentation. Please have a look at CONTRIBUTING.md for more information. See here the list of contributors who participated in this project.

## Publications

If you use this work, please consider citing as follows:

@misc{ifopt,
author       = {Alexander W Winkler},
title        = {{Ifopt - A modern, light-weight, Eigen-based C++ interface to
Nonlinear Programming solvers Ipopt and Snopt.}},
year         = 2018,
doi          = {10.5281/zenodo.1135046},
url          = {https://doi.org/10.5281/zenodo.1135046}
}


The research project within which this code was developed: * A. W. Winkler, D. Bellicoso, M. Hutter, J. Buchli, Gait and Trajectory Optimization for Legged Systems through Phase-based End-Effector Parameterization, IEEE Robotics and Automation Letters (RA-L), 2018:

## Authors

Alexander W. Winkler - Initial Work/Maintainer

This was has been carried out at the following institutions:

#### Linking to custom Ipopt or Snopt

If you are building from source and want to use a locally installed version of Ipopt add the path to your Ipopt build folder to your ~/.bashrc, e.g.

export IPOPT_DIR=/home/your_name/Code/Ipopt-3.12.8/build



In case your OS doesn't provide the precompiled binaries or the required version, you can also easily install Ipopt from source as described here. This summary might work for you:

wget https://www.coin-or.org/download/source/Ipopt/Ipopt-3.11.10.zip
unzip Ipopt-3.11.10.zip
cd Ipopt-3.11.10/ThirdParty/Mumps
./get.Mumps  # HSL routines are faster (http://www.hsl.rl.ac.uk/ipopt/)
cd ../../
mkdir build && cd build
../configure --prefix=/usr/local
make
make test
make install
export IPOPT_DIR=pwd



If you need an interface to Snopt, point cmake to that build folder in your ~/.bashrc through e.g.

export SNOPT_DIR=/home/your_name/Code/Snopt



and run cmake as

cmake -DBUILD_SNOPT=ON ..



# Contributing to ifopt

We are grateful to anyone who decides to actively engage in this project. This project and everyone participating in it is governed by the Code of Conduct. By participating, you are expected to uphold this code.

## Question or Issue?

• ROS Answers: If you want to ask a general usage question, please do this at ROS Answers using the tag ifopt. Asking there has the following advantages:

• There are many more people reading questions there so your chances on getting an answer and in a timely manner are much higher.
• In the future other users will search there for similar problems and can find your question and the potential answers.
• Issue tracker: In case you want to report bugs, request features or closely related to the code, the Issue tracker in this repo is the way to go.

## How Can I Contribute?

Unsure where to begin contributing to ifopt? You can start by looking through these beginner and help-wanted issues:

• Good first issues - issues which should only require a few lines of code, and a test or two.
• Help wanted issues - issues which should be a bit more involved than beginner issues.

Further ideas might include: - writing interfaces to additional solvers - reporting bugs - enhance documentation - add unit tests