SearcharxivSearch

arXiv subjects

L. V. Nguyen

Publications and source records attributed to L. V. Nguyen.

2 recordsLinked to original sources

Harnessing the power of complex light propagation in multimode fibers for spatially resolved sensing

The propagation of coherent light in multimode optical fibers results in a speckled output that is both complex and sensitive to environmental effects. These properties can be a powerful tool for sensing, as small perturbations lead to significant changes in the output of the fiber. However, the mechanism to encode spatially resolved sensing information into the speckle pattern and the ability to extract this information is thus far unclear. In this paper, we demonstrate that spatially dependent mode coupling is crucial to achieving spatially resolved measurements. We leverage machine learning to quantitatively extract this spatially resolved sensing information from three fiber types with dramatically different characteristics and demonstrate that the fiber with the highest degree of spatially dependent mode coupling provides the greatest accuracy.

physics.optics

Stag hunt game-based approach for cooperative UAVs

Unmanned aerial vehicles (UAVs) are being employed in many areas such as photography, emergency, entertainment, defence, agriculture, forestry, mining and construction. Over the last decade, UAV technology has found applications in numerous construction project phases, ranging from site mapping, progress monitoring, building inspection, damage assessments, and material delivery. While extensive studies have been conducted on the advantages of UAVs for various construction-related processes, studies on UAV collaboration to improve the task capacity and efficiency are still scarce. This paper proposes a new cooperative path planning algorithm for multiple UAVs based on the stag hunt game and particle swarm optimization (PSO). First, a cost function for each UAV is defined, incorporating multiple objectives and constraints. The UAV game framework is then developed to formulate the multi-UAV path planning into the problem of finding payoff-dominant equilibrium. Next, a PSO-based algorithm is proposed to obtain optimal paths for the UAVs. Simulation results for a large construction site inspected by three UAVs indicate the effectiveness of the proposed algorithm in generating feasible and efficient flight paths for UAV formation during the inspection task.

cs.RO