A survey on autonomous environmental monitoring approaches: towards unifying active sensing and reinforcement learning
D Mansfield, A Montazeri - Frontiers in Robotics and AI, 2024 - frontiersin.org
The environmental pollution caused by various sources has escalated the climate crisis
making the need to establish reliable, intelligent, and persistent environmental monitoring …
making the need to establish reliable, intelligent, and persistent environmental monitoring …
Optimising air quality prediction in smart cities with hybrid particle swarm optimization‐long‐short term memory‐recurrent neural network model
In smart cities, air pollution is a critical issue that affects individual health and harms the
environment. The air pollution prediction can supply important information to all relevant …
environment. The air pollution prediction can supply important information to all relevant …
Monitoring peak pollution points of water resources with autonomous surface vehicles using a pso-based informative path planner
MJ Ten Kathen, P Johnson, IJ Flores… - Mobile Robot: Motion …, 2023 - Springer
The preservation of water resources is an increasingly urgent issue. Therefore, monitoring
the water quality of these resources is a very important task so that appropriate actions could …
the water quality of these resources is a very important task so that appropriate actions could …
A Novel Variable Step-size Path Planning Framework with Step-Consistent Markov Decision Process For Large-Scale UAV Swarm
D Xu, Y Guo, H Long, C Wang - 2024 IEEE/RSJ International …, 2024 - ieeexplore.ieee.org
In recent years, Deep Reinforcement Learning (DRL) has been a key approach to solving
Unmanned Aerial Vehicle (UAV) swarm path planning problems. However, traditional DRL …
Unmanned Aerial Vehicle (UAV) swarm path planning problems. However, traditional DRL …
[PDF][PDF] Deep reinforcement learning for urban modeling: morphogenesis simulation of self-organized settlements
HE H'sain - 2023 - repository.bilkent.edu.tr
The agents consistently learn to sequentially grow the settlements while adapting their
morphology to maximize performance, maintain right-of-way, and adapt to topographic …
morphology to maximize performance, maintain right-of-way, and adapt to topographic …
Transformer-enabled deep reinforcement learning for coverage path planning
DB Tiu - 2024 - search.proquest.com
Coverage path planning (CPP) is the problem of covering all points in an environment and is
a well-researched topic in robotics due to its sheer practical relevance. This paper …
a well-researched topic in robotics due to its sheer practical relevance. This paper …
DCLPP: A Distributed and Cooperative approach based on Local Path Planning for Multi-sensors Patrolling-Application to Rapid Bushfire Detection
TF Elie, NP Doris-Khöler, ALNN Aziz… - 2021 International …, 2021 - ieeexplore.ieee.org
This study aims to show that rapid detection of fire risk areas in a forest can be done by
keeping the forest under constant and regular surveillance by a small number of mobile …
keeping the forest under constant and regular surveillance by a small number of mobile …