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A Survey on Navigation Approaches for Automated Guided Vehicle Robots in Dynamic Surrounding
, Wan Rahiman,

Automated Guided Vehicles (AGV) have received a lot of attention in recent years in terms of both hardware and software research. Nowadays, the AGV offers more adaptable and effective industrial and transportation system solutions. An AGV’s navigation technique is essential to its operation. The decision to use AGV navigation is not straightforward, even if it appears appropriate and sufficient. This paper surveys the navigation approaches applied to AGV in the past five years of published academic research. In doing so, this work responds to three related questions: 1) are the AGV’s classical navigation techniques still relevant to the current application area?; 2) are heuristic navigation techniques themselves able to optimize AGV movement in terms of guide and strategy?; and 3) is the use of artificial intelligence (AI) in AGV navigation techniques able to increase system performance? As a result, numerous techniques for AGV navigation have been developed globally. On the other hand, the most popular navigation approaches are provided below for more research.

"Automated guided vehicle , classical navigation , SLAM , Lidar , heuristic navigation , A-star , D-star lite , Dijkstra , artificial intelligence , fuzzy logic , neural network , particle swarm optimization , genetic algorithm"
Journal or Conference Name
IEEE Access
Publication Year