collaborators

7 papers

cs.CV2026

FlameVQA: A Physically-Grounded UAV Wildfire VQA Benchmark with Radiometric Thermal Supervision

Mobin Habibpour, John Spodnik, Niloufar Alipour Talemi +1

Wildfire monitoring from UAVs requires reliable reasoning over complex aerial scenes, where smoke, scale variation, and occlusions often limit RGB-only interpretation. We introduce…

cs.CV2026

WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring

Mobin Habibpour, Niloufar Alipour Talemi, John Spodnik +2

Wildfire monitoring requires timely, actionable situational awareness from airborne platforms, yet existing aerial visual question answering (VQA) benchmarks do not evaluate wildfi…

cs.RO2026

FIRE-VLM: A Vision-Language-Driven Reinforcement Learning Framework for UAV Wildfire Tracking in a Physics-Grounded Fire Digital Twin

Chris Webb, Mobin Habibpour, Mayamin Hamid Raha +3

Wildfire monitoring demands autonomous systems capable of reasoning under extreme visual degradation, rapidly evolving physical dynamics, and scarce real-world training data. Exist…

cs.RO2025

Think, Remember, Navigate: Zero-Shot Object-Goal Navigation with VLM-Powered Reasoning

Mobin Habibpour, Fatemeh Afghah

While Vision-Language Models (VLMs) are set to transform robotic navigation, existing methods often underutilize their reasoning capabilities. To unlock the full potential of VLMs…

cs.RO2025

RSV-SLAM: Toward Real-Time Semantic Visual SLAM in Indoor Dynamic Environments

Mobin Habibpour, Alireza Nemati, Ali Meghdari +2

Simultaneous Localization and Mapping (SLAM) plays an important role in many robotics fields, including social robots. Many of the available visual SLAM methods are based on the as…

cs.HC2025

FIRETWIN: Digital Twin Advancing Multi-Modal Sensing, Interactive Analytics for Wildfire Response

Mayamin Hamid Raha, Ali Reza Tavakkoli, Chris Webb +4

Current wildfire management systems lack integrated virtual environments that combine historical data with immersive digital representations, hindering deep analysis and effective…