Research pillars
Autonomous systems
Research on intelligent vehicles and robots, especially policy learning for navigation in complex environments.
- Autonomous driving in simulated and real-world-inspired environments
- Imitation learning, GAIL, EBMs, and diffusion models
- Bird’s-Eye View representations and mid-level perception
- Robust policy generalization under multimodal behaviors
PINC and physics-informed control
Development of models that incorporate physical laws into learning for simulation and control.
- Physics-informed neural networks for ODE/PDE-governed systems
- Control of nonlinear and controllable dynamical systems
- Physics-informed recurrent and reservoir-based models
- Bridging data efficiency, prior knowledge, and control performance
News
Members
Selected publications
See full list (with PDFs) →Collaboration
Research videos & demos
Alumni
- Leonardo Pezenatto da Silva Master — VISERCM: Vision-based Inertial Signal Estimation and Road Condition Monitoring (2026)
- Bruno Maciel Machado Master — Diffusion Models for Offline Behavior Cloning in Autonomous Driving Scenarios (2025)
- Willian Benoski Master — Implicit Behavioral Cloning for Multimodal Behavior Learning in Autonomous Driving (2025)
- Gustavo Claudio Karl Couto Master — Generative Adversarial Imitation Learning with Bird’s-Eye View Input Generation for Autonomous Driving on Urban Environments (2023)
- Irving Giovani Master — Imitation Learning for Autonomous Driving: Disagreement-Regularization and Behavior Cloning with Beta Distribution (2023)
- Eric Mochiutti Master — Physics-Informed Echo State Networks for Modeling Controllable Dynamical Systems (2023)
- Rafael de Souza Toledo Master — Semantic Segmentation of Low-Resolution Images from Damaged Roads (2022)
Funding & institutional support
Apoio · Funding support
CNPq — research projects and scholarships. CAPES — graduate scholarships (MSc/PhD). FAPESC — PhD scholarship.
Host institution
Federal University of Santa Catarina (UFSC), Florianópolis, Brazil.
Contact
Eric Aislan Antonelo
Department of Automation and Systems Engineering (EAS), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil.
Email: