Networking and software design principles converge currently under the notions of Software-Defined Networking (SDN) and Network Function Virtualization (NFV). This means that network services are not anymore static and manually configured, but they become flexible and in the end virtualized components. This convergence enables to dynamically orchestrate the network, to move network functions to the cloud and to direct and prioritize traffic intelligently. Applying cloud principles to network services, configuration and management requires mechanisms for automation, virtualization and elasticity. Ultimately, network services may improve the customer experience for the end users requiring on-demand network resources. The Cross-Layer Orchestrator (CLO) presented in this paper, establishes a tie between the Application and the Network Layers. Through the proposed Cross Layer API, the CLO provides an interface for client and server side applications to reserve, alter and release network resources. Our solution makes the network more dynamic by extending the orchestration functionalities not only to provide on-demand provisioning of network services, but also network flows. In this way the network should be able to adapt accordingly to the requirements of the applications
The proposed bin-picking method combines object recognition with path planning. To avoid conflicts between the assumptions of the elemental techniques needed for bin-picking, object recognition i s combined with path planning by using environmental information. To achieve this combination, a Hough transform, which records the model-to-image matches in a Hough space, is used to estimate the pose. The matches represent the arrangement of the objects, so they can be regaded as environmental information for path planning. To reduce the number of recognition errors and the object-detection time, a pair of object features that reduces the number of invalid votes in the Hough space is used for the Hough transform. Simulated path planning showed that using a Hough space to represent the environmental information improves the ability to plan a safe path for the manipulator. Simulated object recognition showed that using a pair of features makes the process faster and reduces the number of invalid votes. The pose estimation and safe path planning ability were confirmed by an ezperiment on casting objects using a range finder and a robot.
No abstract
Mobile Remote Presence (MRP) system that uses a smart device such as smartphone and tablet pc as video conferencing equipment is getting popular. There are varieties of smart devices, and the appearance of a smart device varies from one to another. We assumed that the appropriate interpersonal distance for an MRP system varies depending on the appearance of the smart device. To confirm our assumption, we conducted a preliminary experiment. The result of the experiment suggested that the value of the proper interpersonal distance increases as the video size increases. It is known that the task load of the remote operator of the MRP system increases if the operator is forced to manually control the MRP system to keep the interpersonal distance to the appropriate level, which adversely affects the quality of the communication through MRP. To resolve the problem, we propose PoliTel, a novel MRP system which autonomously adjusts the interpersonal distance according to the appearance of the smart device by controlling the position or video size of MRP, and allows the operator to concentrate more on the conversation with the person facing to the MRP system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.