Fatrop is a constrained nonlinear optimal control problem solver that is fast and achieves a high numerical robustness.
The main features of the solver are:
- high numerical robustness thanks to advanced numerical optimization techniques, inspired by Ipopt
- fast by exploiting the optimal control problem structure through a specialized linear solver, based on a generalized Riccati recursion
- effective handling of path equality and inequality constraints, without relying on penalty methods
- ability to incorporate exact Lagrangian Hessian information
- ability to be initialized from any, possibly infeasible, solution estimate
A new version of FATROP is on its way.
The release is currently in the beta phase and available for preview in the fatropv1 branch.
- fatrop can be used using the "low-level" interface by implementing an OcpAbstract class. See fatrop/ocp/OCPAbstract.hpp
- fatrop is also interfaced with CasADi. A version without blasfeo CPU specialization is distributed through Pypi and conda. A usage example can be found here.
To cite Fatrop in your academic work, please use the following reference:
@inproceedings{vanroye2023fatrop,
title={Fatrop: A fast constrained optimal control problem solver for robot trajectory optimization and control},
author={Vanroye, Lander and Sathya, Ajay and De Schutter, Joris and Decr{\'e}, Wilm},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={10036--10043},
year={2023},
organization={IEEE}
}
Fatrop is developed by Lander Vanroye at the KU Leuven Robotics Research Group under supervision of Wilm Decre.
Contributors:
- Ajay Sathya (rockit interface)
- The Fatrop logo was designed by Louis Callens