5 papers
Exploring multimodal implicit behavior learning for vehicle navigation in simulated cities
Eric Aislan Antonelo, Gustavo Claudio Karl Couto, Christian Möller
Standard Behavior Cloning (BC) fails to learn multimodal driving decisions, where multiple valid actions exist for the same scenario. We explore Implicit Behavioral Cloning (IBC) w…
An Initial Study of Bird's-Eye View Generation for Autonomous Vehicles using Cross-View Transformers
Felipe Carlos dos Santos, Eric Aislan Antonelo, Gustavo Claudio Karl Couto
Bird's-Eye View (BEV) maps provide a structured, top-down abstraction that is crucial for autonomous-driving perception. In this work, we employ Cross-View Transformers (CVT) for l…
Physics-Informed Neural Networks for Control of Single-Phase Flow Systems Governed by Partial Differential Equations
Luis Kin Miyatake, Eduardo Camponogara, Eric Aislan Antonelo +1
The modeling and control of single-phase flow systems governed by Partial Differential Equations (PDEs) present challenges, especially under transient conditions. In this work, we…
Physics-Informed Echo State Networks for Modeling Controllable Dynamical Systems
Eric Mochiutti, Eric Aislan Antonelo, Eduardo Camponogara
Echo State Networks (ESNs) are recurrent neural networks usually employed for modeling nonlinear dynamic systems with relatively ease of training. By incorporating physical laws in…
A Performance Increment Strategy for Semantic Segmentation of Low-Resolution Images from Damaged Roads
Rafael S. Toledo, Cristiano S. Oliveira, Vitor H. T. Oliveira +2
Autonomous driving needs good roads, but 85% of Brazilian roads have damages that deep learning models may not regard as most semantic segmentation datasets for autonomous driving…