Deep neural network-based multi-stage autonomous guided vehicles trajectory optimization in material transfer systems
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Published online on October 23, 2025
Abstract
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
This article primarily focuses on the design, testing, and validation of a deep neural network (DNN)-based control scheme for predicting multi-stage trajectory optimization in autonomous ground vehicles (AGVs) used in material transportation systems. The ...
This article primarily focuses on the design, testing, and validation of a deep neural network (DNN)-based control scheme for predicting multi-stage trajectory optimization in autonomous ground vehicles (AGVs) used in material transportation systems. The ...