An Online Learning Framework for Uav Search Mission in Adversarial Environments
N Khial, N Mhaisen, M Mabrok, A Mohamed - Available at SSRN 4725375 - papers.ssrn.com
The rapid evolution of Unmanned Aerial Vehicles (UAVs) has revolutionized target search
operations in various fields, including military applications, search and rescue missions, and …
operations in various fields, including military applications, search and rescue missions, and …
Deep reinforcement learning for adaptive exploration of unknown environments
A Peake, J McCalmon, Y Zhang… - 2021 International …, 2021 - ieeexplore.ieee.org
Autonomous exploration is an essential task for unmanned aerial vehicles (UAVs) operating
in unknown environments. Often, UAVs on these missions must first build a map of the …
in unknown environments. Often, UAVs on these missions must first build a map of the …
Deep-reinforcement-learning-based autonomous UAV navigation with sparse rewards
Unmanned aerial vehicles (UAVs) have the potential in delivering Internet-of-Things (IoT)
services from a great height, creating an airborne domain of the IoT. In this article, we …
services from a great height, creating an airborne domain of the IoT. In this article, we …
Online deep reinforcement learning for autonomous UAV navigation and exploration of outdoor environments
BG Maciel-Pearson, L Marchegiani, S Akcay… - arXiv preprint arXiv …, 2019 - arxiv.org
With the rapidly growing expansion in the use of UAVs, the ability to autonomously navigate
in varying environments and weather conditions remains a highly desirable but as-of-yet …
in varying environments and weather conditions remains a highly desirable but as-of-yet …
UAV Control Method Combining Reptile Meta-Reinforcement Learning and Generative Adversarial Imitation Learning
Reinforcement learning (RL) is pivotal in empowering Unmanned Aerial Vehicles (UAVs) to
navigate and make decisions efficiently and intelligently within complex and dynamic …
navigate and make decisions efficiently and intelligently within complex and dynamic …
Learning multi-pursuit evasion for safe targeted navigation of drones
J Xiao, M Feroskhan - IEEE Transactions on Artificial …, 2024 - ieeexplore.ieee.org
Safe navigation of drones in the presence of adversarial physical attacks from multiple
pursuers is a challenging task. This paper proposes a novel approach, asynchronous …
pursuers is a challenging task. This paper proposes a novel approach, asynchronous …
Deep-learning based autonomous-exploration for UAV navigation
Abstract Unmanned Aerial Vehicles (UAVs), functioning as aerial robots, undertake
multifarious missions within intricate and uncharted environments, necessitating …
multifarious missions within intricate and uncharted environments, necessitating …
A combinatorial bandit approach to UAV-aided edge computing
The development of Internet of Things (IoT) leads to an exponential growth of computing
demands. To meet the increasing demand of computation under limited resource, tasks at …
demands. To meet the increasing demand of computation under limited resource, tasks at …
Collision Avoidance for Multiple UAVs in Unknown Scenarios with Causal Representation Disentanglement
J Zhuang, Z Xia, G Han - arXiv preprint arXiv:2407.04064, 2024 - arxiv.org
Deep reinforcement learning (DRL) has achieved remarkable progress in online path
planning tasks for multi-UAV systems. However, existing DRL-based methods often suffer …
planning tasks for multi-UAV systems. However, existing DRL-based methods often suffer …
Goal Conditioned Generative Adversarial Imitation Learning Based on Dueling-DQN
Z Xu, S Wang, K Li - International Conference on Autonomous Unmanned …, 2022 - Springer
Abstract Generative Adversarial Imitation Learning is a powerful and practical approach for
learning sequential decision-making policies. Compared to Reinforcement Learning …
learning sequential decision-making policies. Compared to Reinforcement Learning …