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Particle Swarm Optimization Based Efficient Path Planning in Autonomous Marine Trash Collection
Summary
Researchers developed a marine trash-collecting robot guided by Particle Swarm Optimization (PSO) and GPS, which uses a conveyor-based collection mechanism and sensor input to navigate waterways and efficiently collect floating plastic debris.
This research introduces an innovative solution to marine pollution through the development of a Marine Trash Collector optimized using Particle Swarm Optimization (PSO). Inspired by the collective behavior of bird flocks moving toward areas with abundant food, PSO enables the robot to determine the most efficient path for cleaning water bodies by treating each possible route as a “particle” and optimizing it to minimize time and energy while maximizing trash collection. The robot, powered by an Arduino and guided by a GPS system, uses a conveyor-based mechanism and real-time sensor input to adapt to varying water conditions. When tested, the PSO-optimized model performed better than manual and semi-autonomous modes, collecting more trash in less time and with lower energy consumption. Overall, the system demonstrates strong potential as a scalable, energy-efficient, and intelligent solution for marine waste management, contributing meaningfully to global efforts for cleaner and healthier oceans.
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