collaborators

9 papers

cs.RO2025

UAV-CodeAgents: Scalable UAV Mission Planning via Multi-Agent ReAct and Vision-Language Reasoning

Oleg Sautenkov, Yasheerah Yaqoot, Muhammad Ahsan Mustafa +5

We present UAV-CodeAgents, a scalable multi-agent framework for autonomous UAV mission generation, built on large language and vision-language models (LLMs/VLMs). The system levera…

cs.RO2025

MorphoNavi: Aerial-Ground Robot Navigation with Object Oriented Mapping in Digital Twin

Sausar Karaf, Mikhail Martynov, Oleg Sautenkov +2

This paper presents a novel mapping approach for a universal aerial-ground robotic system utilizing a single monocular camera. The proposed system is capable of detecting a diverse…

cs.RO2025

RaceVLA: VLA-based Racing Drone Navigation with Human-like Behaviour

Valerii Serpiva, Artem Lykov, Artyom Myshlyaev +4

RaceVLA presents an innovative approach for autonomous racing drone navigation by leveraging Visual-Language-Action (VLA) to emulate human-like behavior. This research explores the…

cs.RO2025

CognitiveDrone: A VLA Model and Evaluation Benchmark for Real-Time Cognitive Task Solving and Reasoning in UAVs

Artem Lykov, Valerii Serpiva, Muhammad Haris Khan +5

This paper introduces CognitiveDrone, a novel Vision-Language-Action (VLA) model tailored for complex Unmanned Aerial Vehicles (UAVs) tasks that demand advanced cognitive abilities…

cs.RO2025

UAV-VLRR: Vision-Language Informed NMPC for Rapid Response in UAV Search and Rescue

Yasheerah Yaqoot, Muhammad Ahsan Mustafa, Oleg Sautenkov +3

Emergency search and rescue (SAR) operations often require rapid and precise target identification in complex environments where traditional manual drone control is inefficient. In…

cs.RO2025

UAV-VLPA*: A Vision-Language-Path-Action System for Optimal Route Generation on a Large Scales

Oleg Sautenkov, Aibek Akhmetkazy, Yasheerah Yaqoot +4

The UAV-VLPA* (Visual-Language-Planning-and-Action) system represents a cutting-edge advancement in aerial robotics, designed to enhance communication and operational efficiency fo…