A Bayesian optimized variational mode decomposition-based denoising method for measurement while drilling signal of down-the-hole drilling
W Ding, S Hou, S Tian, S Liang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Measurement while drilling (MWD) emerges as a reliable technique for assessing rock mass
properties. However, the measured MWD signals are often contaminated with noise, leading …
properties. However, the measured MWD signals are often contaminated with noise, leading …
Coordinated route planning of multiple fuel-constrained unmanned aerial systems with recharging on an unmanned ground vehicle for mission coverage
Abstract Small Unmanned Aerial Systems (sUAS) such as quadcopters are ideal for aerial
surveillance because of their runway independence, terrain-agnostic maneuverability, low …
surveillance because of their runway independence, terrain-agnostic maneuverability, low …
Cooperative multi-agent planning framework for fuel constrained uav-ugv routing problem
Abstract Unmanned Aerial Vehicles (UAVs), adept at aerial surveillance, are often
constrained by their limited battery capacity. Refueling on slow-moving Unmanned Ground …
constrained by their limited battery capacity. Refueling on slow-moving Unmanned Ground …
A Bayesian Optimization Approach for Tuning a Grou** Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems
Background: The Multi Depot Pickup and Delivery Problem with Time Windows and
Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing …
Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing …
A robust uav-ugv collaborative framework for persistent surveillance in disaster management applications
Unmanned Aerial Vehicles (UAVs) are fast, agile, and capable of covering large areas
quickly but are constrained by their limited fuel capacities. In contrast, Unmanned Ground …
quickly but are constrained by their limited fuel capacities. In contrast, Unmanned Ground …
An Attention-aware Deep Reinforcement Learning Framework for UAV-UGV Collaborative Route Planning
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 …
operational range is limited by their battery capacity. Deploying mobile recharging stations …
Swarm Intelligence in Action: Particle Swarm Optimization and Rendezvous Algorithms for Swarm Robotics
Swarm technology is evolving quickly in the new era in the domains of autonomous
underwater vehicles (AUVs), unmanned aerial vehicles (UAVs), and unmanned ground …
underwater vehicles (AUVs), unmanned aerial vehicles (UAVs), and unmanned ground …
Geometric zoning and selective routing for surveillance and coverage operations
Taking fast action, and effectively utilizing the available resources, are important when
conducting time-critical surveillance missions. In addition, the potential complexity of the …
conducting time-critical surveillance missions. In addition, the potential complexity of the …
Iterative Planning for Multi-Agent Systems: An Application in Energy-Aware UAV-UGV Cooperative Task Site Assignments
This paper presents an iterative planning framework for multi-agent systems with hybrid
state spaces. The framework uses transition systems to mathematically represent planning …
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)
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 …
moving unmanned ground vehicles (UGVs) to cooperatively perform tasks over wide areas …