A robust strategy for uav autonomous landing on a moving platform under partial observability

G Aikins, S Jagtap, KD Nguyen - Drones, 2024‏ - mdpi.com
Landing a multi-rotor uncrewed aerial vehicle (UAV) on a moving target in the presence of
partial observability, due to factors such as sensor failure or noise, represents an …

Integrated learning-based framework for autonomous quadrotor UAV landing on a collaborative moving UGV

C Wang, J Wang, Z Ma, M Xu, K Qi… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Autonomous unmanned aerial vehicle (UAV) landing on a moving unmanned ground
vehicle (UGV) remains a challenge as it is difficult for the UAV to track the real-time state of …

Vision-based algorithm for autonomous aerial landing

AES Morando, MF Santos, P Castillo… - 2024 International …, 2024‏ - ieeexplore.ieee.org
The landing phase is a critical stage in autonomous aerial landing, especially when the
aerial vehicle lands in a moving platform, as ground vehicles. In this paper, a solution …

AgentForge: A Flexible Low-Code Platform for Reinforcement Learning Agent Design

FEF Junior, A Oulasvirta - ar** a reinforcement learning (RL) agent often involves identifying values for
numerous parameters, covering the policy, reward function, environment, and agent-internal …

Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective

Q Liu, J Gao, D Zhu, Z Qiao, P Chen, J Guo… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Multi-agent target assignment and path planning (TAPF) are two key problems in intelligent
warehouse. However, most literature only addresses one of these two problems separately …

SafeSwarm: Decentralized Safe RL for the Swarm of Drones Landing in Dense Crowds

G Tadevosyan, M Osipenko, D Aschu… - arxiv preprint arxiv …, 2025‏ - arxiv.org
This paper introduces a safe swarm of drones capable of performing landings in crowded
environments robustly by relying on Reinforcement Learning techniques combined with …