Routing UAVs in landslides Monitoring: A neural network heuristic for team orienteering with mandatory visits

C Fang, Z Han, W Wang, E Zio - Transportation Research Part E: Logistics …, 2023 - Elsevier
Unmanned aerial vehicles (UAVs) are widely used for surveillance in both civilian and
military scenarios. The utilization of UAVs provides an opportunity for monitoring landslide …

Optimizing Drone Delivery Paths from Shared Bases: A Location-Routing Problem with Realistic Energy Constraints

M Meskar, A Ahmadi-Javid - Journal of Intelligent & Robotic Systems, 2024 - Springer
Recently, Amazon patented fulfillment centers for drones on a large scale in densely
populated areas. A network of such shared centers can be used for landing and launching …

Iterative Planning for Multi-Agent Systems: An Application in Energy-Aware UAV-UGV Cooperative Task Site Assignments

N Thelasingha, AA Julius, J Humann… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
This paper presents an iterative planning framework for multi-agent systems with hybrid
state spaces. The framework uses transition systems to mathematically represent planning …

Solving Vehicle Routing Problem for Unmanned Heterogeneous Vehicle Systems using Asynchronous Multi-Agent Architecture (A-teams)

S Ramasamy, MS Mondal… - 2023 International …, 2023 - ieeexplore.ieee.org
Fast moving but power hungry unmanned aerial vehicles (UAVs) can recharge on slow-
moving unmanned ground vehicles (UGVs) to cooperatively perform tasks over wide areas …

Deep Learning–based Reassembling of an Aerial & Legged Marsupial Robotic System–of–Systems

P Arora, T Karakurt, E Avlonitis… - 2023 International …, 2023 - ieeexplore.ieee.org
In this work we address the System-of-Systems reassembling operation of a marsupial team
comprising a hybrid Unmanned Aerial Vehicle and a Legged Locomotion robot, relying …

Use of the DIBR-grey EDAS model of MCDM to the selection of a combat unmanned ground platform

M Radovanović, D Božanić… - Operations …, 2024 - orel.unionnikolatesla.edu.rs
The paper presents a hybrid model of choosing a combat unmanned ground platform using
the DIBR and grey–EDAS (G-EDAS) method. This model has been tested and confirmed on …

Geometric zoning and selective routing for surveillance and coverage operations

M El Yafrani, DK Kılıç, F Miehe… - Engineering …, 2024 - Taylor & Francis
Taking fast action, and effectively utilizing the available resources, are important when
conducting time-critical surveillance missions. In addition, the potential complexity of the …

An Attention-aware Deep Reinforcement Learning Framework for UAV-UGV Collaborative Route Planning

MS Mondal, S Ramasamy, JD Humann… - 2024 IEEE/RSJ …, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) possess the capability to survey vast areas, yet their
operational range is limited by their battery capacity. Deploying mobile recharging stations …

OptiRoute: A Heuristic-assisted Deep Reinforcement Learning Framework for UAV-UGV Collaborative Route Planning

MS Mondal, S Ramasamy, P Bhounsule - arXiv preprint arXiv:2309.09942, 2023 - arxiv.org
Unmanned aerial vehicles (UAVs) are capable of surveying expansive areas, but their
operational range is constrained by limited battery capacity. The deployment of mobile …

Optimizing Routes of Heterogenous Unmanned Systems using Supervised Learning in a Multi-Agent Framework: A computational study

S Ramasamy, MS Mondal, JD Humann… - 2024 International …, 2024 - ieeexplore.ieee.org
Fast-paced but power-hungry Unmanned Aerial Vehicles (UAV) may collaborate with slow-
paced Unmanned Ground Vehicles (UGV) acting as mobile recharging depots to perform …