Research

Daniel's research areas are Model Predictive Control (MPC), optimization, and motion planning. Currently the MPC research is focused on problems related to real-time MPC. Ongoing research relates to efficient linear algebra for on-line algorithms, parametric programming, parallel computations, as well as real-time constrained optimization. The research about motion planning includes theoretical aspects, algorithms, and applications. Current industry research partners are Scania CV and Saab Dynamics. Daniel's research is financed by the Swedish Research Council, ELLIIT, EOARD, FFI and WASP/KAW.

Daniel has been the main supervisor of the following now graduated Ph.D. students: Dr. Isak Nielsen, Dr. Oskar Ljungqvist, Dr. Kristoffer Bergman, Dr. Daniel Arnström, Lic. Niclas Evestedt, Lic. Jonas Nordlöf. He has been the supervisor of the post-doc Dr. Syed Amrr.

Daniel is currently the main supervisor of the following Ph.D. students: Shamisa Shoja, and Anja Hellander. He is also currently the co-supervisor of Luca Lebon. Furthermore, he is currently the supervisor of the post-doc Dr. Abhishek Dhar.

Daniel's research has resulted in the following open source software for embedded quadratic programming and exact complexity certification implemented by Daniel Arnström: daqp and ASCertain.jl.

Daniel recently took part in the ELLIIT tech talks. A popular scientific presentation followed by an interview by Johan Wester is available here: