Robot motion planning with uncertainty in control and sensing
Artificial Intelligence
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
Dynamic data driven application simulation of surface transportation systems
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
Distributed dynamic data driven prediction based on reinforcement learning approach
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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With advance in distributed system technology, data has become ubiquitous and its dynamics has increased. Therefore, in this paper we proposed a new framework to integrate dynamic data driven application systems (DDDAS) with service-oriented architecture (SOA) and web services technology to tackle dynamic data issue in a real-time environment. An efficient and effective service-oriented dynamic data-driven framework algorithm is designed to support a prediction strategy for vehicle navigation. The simulation results show that our algorithm outperforms the Dijkstra algorithm by improving 24.43% in average vehicle traveling time.