most citedThe NavINST Dataset for Multi-Sensor Autonomous Navigation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.RO2026

Navigation by Skylight Polarization via Rayleigh Model Optimization on a Road Vehicle

Ben Potter, Eslam Mounier, Aboelmagd Noureldin +2

Reliable absolute heading estimation is critical for road-vehicle navigation, particularly when magnetic, inertial, or GNSS-based references are degraded. This paper presents a sky…

cs.RO2026

Building A Multi-Sensor Platform For Autonomous Driving Research: Challenges and Lessons Learned

Paulo Ricardo Marques de Araujo, Eslam Mounier, Qamar Bader +2

This paper reports on the challenges encountered and lessons learned during the development and deployment of a flexible multi-sensor platform for autonomous driving research. It a…

eess.SP2026

Differential LEO Navigation under Asynchronous Satellite Clocks: Architecture and Performance Bounds

Qamar Bader, Sharief Saleh, Henk Wymeersch +2

Low Earth Orbit (LEO) communication satellites have emerged as a promising source of signals of opportunity for resilient positioning, navigation, and timing (PNT) in GNSS-challeng…

cs.MA2026

ARMATA: Auto-Regressive Multi-Agent Task Assignment

Yazan Youssef, Aboelmagd Noureldin, Sidney Givigi

Coordinating multi-agent systems over spatially distributed areas requires solving a complex hierarchical problem: first distributing areas among agents (allocation) and subsequent…

cs.RO2025

Look to Locate: Vision-Based Multisensory Navigation with 3-D Digital Maps for GNSS-Challenged Environments

Ola Elmaghraby, Eslam Mounier, Paulo Ricardo Marques de Araujo +1

In Global Navigation Satellite System (GNSS)-denied environments such as indoor parking structures or dense urban canyons, achieving accurate and robust vehicle positioning remains…

cs.RO2025★ 1 cited

The NavINST Dataset for Multi-Sensor Autonomous Navigation

Paulo Ricardo Marques de Araujo, Eslam Mounier, Qamar Bader +5

The NavINST Laboratory has developed a comprehensive multisensory dataset from various road-test trajectories in urban environments, featuring diverse lighting conditions, includin…