Print Email Facebook Twitter Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Wind Title Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Wind Author Bos, F.R.R.C. (Student TU Delft) Anil Meera, A. (TU Delft Robot Dynamics) Benders, D. (TU Delft Learning & Autonomous Control) Wisse, M. (TU Delft Robot Dynamics) Date 2022 Abstract The free energy principle from neuroscience provides a brain-inspired perception scheme through a data-driven model learning algorithm called Dynamic Expectation Maximization (DEM). This paper aims at introducing an exper-imental design to provide the first experimental confirmation of the usefulness of DEM as a state and input estimator for real robots. Through a series of quadcopter flight experiments under unmodelled wind dynamics, we prove that DEM can leverage the information from colored noise for accurate state and input estimation through the use of generalized coordinates. We demonstrate the superior performance of DEM for state es-timation under colored noise with respect to other benchmarks like State Augmentation, SMIKF and Kalman Filtering through its minimal estimation error. We demonstrate the similarities in the performance of DEM and Unknown Input Observer (UIO) for input estimation. The paper concludes by showing the influence of prior beliefs in shaping the accuracy-complexity trade-off during DEM's estimation. Subject Estimation errorNeuroscienceFilteringHeuristic algorithmsRobot kinematicsObserversBenchmark testing To reference this document use: http://resolver.tudelft.nl/uuid:2c54175e-5757-468c-b4c9-533bcb9b6811 DOI https://doi.org/10.1109/ICRA46639.2022.9812415 Publisher IEEE Embargo date 2023-07-01 ISBN 978-1-7281-9681-7 Source Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2022 Event 39th IEEE International Conference on Robotics and Automation, ICRA 2022, 2022-05-23 → 2022-05-27, Philadelphia, United States Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type conference paper Rights © 2022 F.R.R.C. Bos, A. Anil Meera, D. Benders, M. Wisse Files PDF Free_Energy_Principle_for ... n_Wind.pdf 1.55 MB Close viewer /islandora/object/uuid:2c54175e-5757-468c-b4c9-533bcb9b6811/datastream/OBJ/view