21 citations · 42 across the 6 of their papers we have counts for
6 papers
Towards Dependable Autonomous Systems Based on Bayesian Deep Learning Components
Fabio Arnez, Huascar Espinoza, Ansgar Radermacher +1
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estim…
Design Considerations of an Unmanned Aerial Vehicle for Aerial Filming
Dennis Casazola, Fabio Arnez, Huascar Espinoza
Filming sport videos from an aerial view has always been a hard and an expensive task to achieve, especially in sports that require a wide open area for its normal development or t…
Quantifying and Using System Uncertainty in UAV Navigation
Fabio Arnez, Ansgar Radermacher, Huascar Espinoza
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estim…
Improving Robustness of Deep Neural Networks for Aerial Navigation by Incorporating Input Uncertainty
Fabio Arnez, Huascar Espinoza, Ansgar Radermacher +1
Uncertainty quantification methods are required in autonomous systems that include deep learning (DL) components to assess the confidence of their estimations. However, to successf…
Optimized Execution of PDDL Plans using Behavior Trees
Francisco Martín, Matteo Morelli, Huascar Espinoza +2
Robots need task planning to sequence and execute actions toward achieving their goals. On the other hand, Behavior Trees provide a mathematical model for specifying plan execution…
A Comparison of Uncertainty Estimation Approaches in Deep Learning Components for Autonomous Vehicle Applications
Fabio Arnez, Huascar Espinoza, Ansgar Radermacher +1
A key factor for ensuring safety in Autonomous Vehicles (AVs) is to avoid any abnormal behaviors under undesirable and unpredicted circumstances. As AVs increasingly rely on Deep N…