Internet of Things and artificial intelligence technology are the key elements of the intelligent construction of iron and steel production warehouse. This paper puts forward a whole set of intelligent scheme for bar ...Internet of Things and artificial intelligence technology are the key elements of the intelligent construction of iron and steel production warehouse. This paper puts forward a whole set of intelligent scheme for bar warehouse crane for the guidance of metallurgical process engineering, including cluster rapid self-awareness technology of the smart crane, precise self-executing technique of crane with rigid-flexible hybrid structure, multi-body system kinematics model of the smart crane sling and the swing characteristics model at different azimuth, antiswing control technology based on the optimization objective function, the vehicle model recognition system based on lidar, and the clustering crane dynamic scheduling method based on multi-agent reinforcement learning. The complete intelligent logistics system of the bar warehouse has changed the original operation mode of the warehouse area and realized the unmanned operation and intelligent scheduling of the crane,which is of great significance for improving the production efficiency, reducing the production cost, and improving the product quality.展开更多
In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemina...In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemina- tion system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information （e.g., identifying the real travel path）, as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type （i.e., elevated or ground road） of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algo- rithm.展开更多
基金financially supported by the National Key Research and Development Plan of China (No.2020YFB1713600)the National Natural Science Foundation of China (No.51975043)the Fundamental Research Funds for the Central Universities (Nos.FRF-TP-19002A3 and FRF-TP-20-105A1)。
文摘Internet of Things and artificial intelligence technology are the key elements of the intelligent construction of iron and steel production warehouse. This paper puts forward a whole set of intelligent scheme for bar warehouse crane for the guidance of metallurgical process engineering, including cluster rapid self-awareness technology of the smart crane, precise self-executing technique of crane with rigid-flexible hybrid structure, multi-body system kinematics model of the smart crane sling and the swing characteristics model at different azimuth, antiswing control technology based on the optimization objective function, the vehicle model recognition system based on lidar, and the clustering crane dynamic scheduling method based on multi-agent reinforcement learning. The complete intelligent logistics system of the bar warehouse has changed the original operation mode of the warehouse area and realized the unmanned operation and intelligent scheduling of the crane,which is of great significance for improving the production efficiency, reducing the production cost, and improving the product quality.
文摘In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemina- tion system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information （e.g., identifying the real travel path）, as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type （i.e., elevated or ground road） of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algo- rithm.
