Abstract: In this paper, we investigate the methods of multitarget tracking in imaging process, focusing on both point targets and extended targets. Point target imaging is characterized by low signal ...
Abstract: Multiple power peaks are introduced under nonuniform irradiation conditions in photovoltaic (PV) systems. However, conventional maximum power point tracking (MPPT) algorithms, such as the ...
Abstract: Visual simultaneous localization and mapping (VSLAM) as an efficient positioning and navigation solution has been widely used in fields such as unmanned aerial vehicles, robots, and ...
Abstract: To address the issue of low accuracy in 3D point cloud registration, we present a novel iterative closest point (ICP) algorithm for point registration using the stochastic differential ...
Abstract: Autonomous underwater vehicles (AUV) play an important role in the process of human exploration of the ocean. However, the existing AUV control methods are faced with the problem of ...
Abstract: To enhance the multi-target path planning and tracking performance of Unmanned Surface Vehicles (USVs), a combined control strategy integrating the Serret-Frenet Line-of-Sight (SFLOS) ...
Abstract: Formation control algorithms are a prominent area of study in the domain of drones and drone swarms. The goal of the formation control algorithms is to manage and manipulate individuals to ...
Abstract: This paper proposes a new algorithm for choosing a solution in the Pareto Optimal Front of the multi-objective optimization problem of the spectral and energy efficiency trade-off in Massive ...
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Abstract: This study develops a novel end-to-end formation strategy for leader-follower formation control of mobile robots that uses onboard LiDAR sensors in non-communication environments. The main ...
Abstract: To address the problem of slow route computation caused by excessive exploration of unnecessary nodes in traditional A* algorithm combined with the dynamic window approach, as well as the ...
Abstract: Many advanced techniques efficiently harvest the global maximum power (GMP) of the photovoltaic (PV) system, including machine learning techniques and metaheuristic algorithms based maximum ...
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