VRI4WD UFPR-MAP: A Multi-Sensor Dataset with Geodetic Ground-Truth for Wheeled Mobile Robots in Hybrid Environment

• Carlos Eduardo Magrin UFPR https://orcid.org/0009-0004-7734-5573
• Felipe Gustavo Bombardelli UFPR https://orcid.org/0009-0004-5762-0849
• Wander da Cruz UFPR https://orcid.org/0000-0003-0738-1283
• Eduardo Todt UFPR https://orcid.org/0000-0001-6045-1274

Resumo

This paper presents the UFPR-MAP dataset, collected with the VRI4WD mobile robot platform equipped with diverse low-cost sensors, including GNSS, laser scanner, IMU, ultrasound, infrared, encoders, and WLAN signal receivers. Unlike high-end datasets, UFPR-MAP focuses on affordable sensor blend sets for indoor and outdoor environments, validated through rigorous ground-truth via GNSS and total station measurements. The dataset supports research on multi-sensor fusion and wheeled mobile robot localization in varied architectural contexts. The VRI4WD UFPR-MAP dataset is available in https://github.com/VRI-UFPR/ufpr-map.

Palavras-chave: Location awareness, Global navigation satellite system, Wireless LAN, Ultrasonic imaging, Ultrasonic variables measurement, Sensor fusion, Robot sensing systems, Sensors, Trajectory, Mobile robots, dataset, multi-sensor, wheeled mobile robot, geodetic ground-truth