5 papers
AttentionSwarm: Reinforcement Learning with Attention Control Barier Function for Crazyflie Drones in Dynamic Environments
Grik Tadevosyan, Valerii Serpiva, Aleksey Fedoseev +6
We introduce AttentionSwarm, a novel benchmark designed to evaluate safe and efficient swarm control in a dynamic drone racing scenario. Central to our approach is the Attention Mo…
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…
UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation
Oleg Sautenkov, Yasheerah Yaqoot, Artem Lykov +7
The UAV-VLA (Visual-Language-Action) system is a tool designed to facilitate communication with aerial robots. By integrating satellite imagery processing with the Visual Language…
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…
SafeSwarm: Decentralized Safe RL for the Swarm of Drones Landing in Dense Crowds
Grik Tadevosyan, Maksim Osipenko, Demetros Aschu +5
This paper introduces a safe swarm of drones capable of performing landings in crowded environments robustly by relying on Reinforcement Learning techniques combined with Safe Lear…