| 2022 | FUSION | Detection of outliers in classification by using quantified uncertainty in neural networks. | Magnus Malmstrm, Isaac Skog, Daniel Axehill, Fredrik Gustafsson |
| 2022 | FUSION | LiDAR-Landmark Modeling for Belief-Space Planning using Aerial Forest Data. | Jonas Nordlf, Gustaf Hendeby, Daniel Axehill |
| 2021 | FUSION | Modeling of the tire-road friction using neural networks including quantification of the prediction uncertainty. | Magnus Malmstrm, Isaac Skog, Daniel Axehill, Fredrik Gustafsson |
| 2021 | FUSION | Improved Virtual Landmark Approximation for Belief-Space Planning. | Jonas Nordlf, Gustaf Hendeby, Daniel Axehill |
| 2020 | FUSION | Belief Space Planning using Landmark Density Information. | Jonas Nordlf, Gustaf Hendeby, Daniel Axehill |
| 2020 | ICRA | On sensing-aware model predictive path-following control for a reversing general 2-trailer with a car-like tractor. | Oskar Ljungqvist, Daniel Axehill, Henrik Pettersson |
| 2019 | FUSION | Informative Path Planning in the Presence of Adversarial Observers. | Per Bostrm-Rost, Daniel Axehill, Gustaf Hendeby |
| 2016 | IROS | Motion planning for a reversing general 2-trailer configuration using Closed-Loop RRT. | Niclas Evestedt, Oskar Ljungqvist, Daniel Axehill |
| 2015 | FUSION | Extended Kalman filter modifications based on an optimization view point. | Martin A. Skoglund, Gustaf Hendeby, Daniel Axehill |