This approach enhances BC by integrating a kernel density estimator to adjust training sample weights based on action density, thereby improving the learning of rare but critical actions such as stopping at red lights and accelerating at green lights, specially in scenarios of scarce number of expert demonstrations.
Eric A. Antonelo, Gustavo Claudio Karl Couto, Christiane Möller et al.· Brazilian Conference on Inte...· 4 citations
In autonomous driving, Bird's-Eye View (BEV) representations provide a structured, top-down abstraction of the vehicle's surroundings and have become a key input modality for Behavioral Cloning (BC) policies. While ground-truth BEV maps are readily available in simulation, real-world deployment requires replacing them...
Felipe Dos Santos, Eric A. Antonelo, Gustavo Claudio Karl Couto· 0 citations
This paper presents a low-cost, open experimental platform for research in end-to-end autonomous driving with miniature Ackermann vehicles. The platform combines a physical vehicle, a printed urban track, data collection tools, trajectory registration, and a Webots digital twin, enabling controlled experiments that con...
Gustavo Claudio Karl Couto, Eric A. Antonelo, Gabriel George Zipperer· 1 citation
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