LAUSR

Abstract This paper presents an open toolchain tailored for deployment of nonlinear model predictive control for serial robots. The toolchain provides a direct workflow from problem definition to solution deployment on a serial robot based on open-source software. Thus, we provide an insightful selection of modules for rigid body dynamics, numerical optimization, and robot control, and a strategy to make them cooperate in a way that is efficient in terms of computation and engineering time. A detailed numerical study is presented for path-following MPC on a 7-degrees-of-freedom robot, showing the efficiency and ease of use of the presented toolchain while comparing its modules with other tools.