Eduardo E. Veas — accepted AI-conference papers

2025

UN3-Mapping: Uncertainty-Aware Neural Non-Projective Signed Distance Fields for 3D Mapping

Shuangfu Song, Junqiao Zhao, Eduardo E. Veas, Jiaye Lin, Qiuyi Cao, Chen Ye +1

RA-L 2025

Building accurate and reliable maps is a critical requirement for autonomous robots. In this paper, we propose UN3-Mapping, an implicit neural mapping method that enables high-quality 3D reconstruction with integrated uncertainty estimation. Our approach employs a hybrid representation: an implicit

Cited by 0 Source ↗code ↗Scholar ↗

2024

A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data

Adrian Remonda, Nicklas Hansen, Ayoub Raji, Nicola Musiu, Marko Bertogna, Eduardo E. Veas +1

NeurIPS 2024poster

Despite the availability of international prize-money competitions, scaled vehicles, and simulation environments, research on autonomous racing and the control of sports cars operating close to the limit of handling has been limited by the high costs of vehicle acquisition and management, as well as…

Cited by 7 Source ↗PDF ↗code ↗Scholar ↗