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…
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…
TornadoDrone: Bio-inspired DRL-based Drone Landing on 6D Platform with Wind Force Disturbances
Robinroy Peter, Lavanya Ratnabala, Demetros Aschu +2
Autonomous drone navigation faces a critical challenge in achieving accurate landings on dynamic platforms, especially under unpredictable conditions such as wind turbulence. Our r…
MARLander: A Local Path Planning for Drone Swarms using Multiagent Deep Reinforcement Learning
Demetros Aschu, Robinroy Peter, Sausar Karaf +2
Achieving safe and precise landings for a swarm of drones poses a significant challenge, primarily attributed to conventional control and planning methods. This paper presents the…
Lander.AI: Adaptive Landing Behavior Agent for Expertise in 3D Dynamic Platform Landings
Robinroy Peter, Lavanya Ratnabala, Demetros Aschu +2
Mastering autonomous drone landing on dynamic platforms presents formidable challenges due to unpredictable velocities and external disturbances caused by the wind, ground effect,…