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HDec-POSMDPs MRS Exploration and Fire Searching Based on IoT cloud robotics

International Journal of Automation and computing 2020年第3期17卷 364-377页

作者： Ayman El Shenawy Khalil Mohamed Hany Harb Systems and Computers Engineering Department Faculty of EngineeringAl-Azhar UniversityCairo 11751Egypt Information Technology College Misr University for Science and Technology(MUST)Cairo 77Egypt

The multi-robot systems(MRS)exploration and fire searching problem is an important application of mobile robots which require massive computation capability that exceeds the ability of traditional MRS′*** paper propose a cloud-based hybrid decentralized partially observable semi-Markov decision process(HDec-POSMDPs)*** proposed model is implemented for MRS exploration and fire searching application based on the Internet of things(IoT)cloud robotics *** this implementation the heavy and expensive computational tasks are offloaded to the cloud *** proposed model achieves a significant improvement in the computation burden of the whole task relative to a traditional *** proposed model is applied to explore and search for fire objects in an unknown environment;using different sets of robots *** preliminary evaluation of this implementation demonstrates that as the parallelism of computational instances increase the delay of new actuation commands which will be decreased,the mean time of task completion is decreased,the number of turns in the path from the start pose cells to the target cells is minimized and the energy consumption for each robot is reduced.

关键词： Multi-robot systems hybrid decentralized partially observable semi-Markov decision process(HDec-POSMDPs) multi-robot systems(MRS)exploration and fire searching cloud robotics cloud computing

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A Resource Elastic Scheduling Algorithm of Service Platform for cloud robotics 32

A Resource Elastic Scheduling Algorithm of Service Platform ...

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第32届中国控制与决策会议

作者： Ji Peng Chu Hao Chi Jianning Jiang Jingqi Faculty of Robot Science and Engineering Northeastern University

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158556;9781728158563

cloud computing can offer the robots high performance computing resources,and the big data stored on cloud platform can enhance significantly autonomy and collaborative capacity of ***,a platform as a service level cloud platform is essential,which should provide the ability of reusing the achievements of robotics and support that multi robots can access the cloud services on *** ensure that the robots functional services can have a better performance of computing in high or low loads,and improve the resource utilization efficiency of service platform,there is a flexible container capacity scheduling algorithm in the resource management *** the actual operation situation of different robotic services,this algorithm calculates the average load according to the CPU usage,memory usage and network usage of containers,and performs capacity elastic scheduling operation by preset upper and lower *** the period of resource flexibility expansion,users will not perceive the dynamic scheduling of functional service capacity,which ensures the stability of the platform.

关键词： cloud robotics Docker container technology Service Platform Resource elastic scheduling Load balancing

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Robo cloud: augmenting robotic visions for open environment modeling using Internet knowledge

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Science China(Information Sciences) 2018年第5期61卷 19-34页

作者： Yiying LI Huaimin WANG Bo DING Wei ZHOU College of Computer National University of Defense Technology

Modeling an open environment that contains unpredictable objects is a challenging problem in the field of robotics. In traditional approaches, when a robot encounters an unknown object, a mistake will inevitably be added to the robot's environmental model, severely constraining the robot's autonomy,and possibly leading to disastrous consequences in certain settings. The abundant knowledge accumulated on the Internet has the potential to remedy the uncertainties that result from encountering with unknown objects. However, robotic applications generally pay considerable attention to quality of service(Qo S).For this reason, directly accessing the Internet, which can be unpredictable, is generally not *** cloud is proposed as a novel approach to environment modeling that takes advantage of the Internet without sacrificing the critical properties of Qo S. Robo cloud is a "mission cloud–public cloud" layered cloud organization model in which the mission cloud provides Qo S-available environment modeling capability with built-in prior knowledge while the public cloud is the existing services provided by the Internet. The "cloud phase transition" mechanism seeks help from the public cloud only when a request is outside the knowledge of the mission cloud and the Qo S cost is acceptable. We have adopted semantic mapping, a typical robotic environment modeling task, to illustrate and substantiate our approach and key mechanism. Experiments using open 2 D and 3 D datasets with real robots have demonstrated that Robo cloud is able to augment robotic visions for open environment modeling.

关键词： Internet-augmented environment modeling uncertainty robotic visions semantic mapping robotic software cloud robotics

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