An Agent-Based System Integration Architecture for Intelligent Service Robots

2006 ◽  
pp. 6-6
Author(s):  
Jaeho Lee
Keyword(s):  
System Integration ◽  
Service Robots ◽  
Agent Based ◽  
Integration Architecture

An agent-based service-oriented integration architecture for chemical process automation

2015 ◽  
Vol 23 (1) ◽  
pp. 173-180 ◽  
Author(s):  
Na Luo ◽  
Weimin Zhong ◽  
Feng Wan ◽  
Zhencheng Ye ◽  
Feng Qian
Keyword(s):  
Chemical Process ◽  
Process Automation ◽  
Agent Based ◽  
Integration Architecture ◽  
Service Oriented

scholarly journals Overview of Service Interface Design Approaches for Interoperability of Traditional System Integration Patterns

2021 ◽  
Vol 6 (1) ◽  
pp. 44-53
Author(s):  
Norziana Yahya ◽  
Mohd Azahani Md Taib
Keyword(s):  
System Integration ◽  
Interface Design ◽  
Heterogeneous System ◽  
Heterogeneous Systems ◽  
Design Stage ◽  
Legacy Systems ◽  
Distributed Objects ◽  
Traditional System ◽  
Integration Architecture ◽  
Service Interface

One of the major issues in system integration is to deal with interoperability of legacy systems which use traditional System Integration Patterns (SIP). Information are unable to exchange effectively when the systems involved comes from developer that tended to not interoperate and this leads to the interoperability problem in heterogeneous system integration. To address the interoperability issues, interfacing processes need to be made more easily by defining components, processes, and interfaces that affect the system integration architecture at the initial design stage. This paper includes a basic concept on types of traditional SIP covering File-Based, Common Database, Remote Procedure Call (RPC), Distributed Objects, and Messaging. An overview of three Service Interface Design (SID) approaches for systems interoperability is discussed. The discussions on these approaches serve as a basis for the solution of interoperability of heterogeneous systems which use traditional SIP.

scholarly journals Robot Partner Development Platform for Human-Robot Interaction Based on a User-Centered Design Approach

2020 ◽  
Vol 10 (22) ◽  
pp. 7992
Author(s):  
Jinseok Woo ◽  
Yasuhiro Ohyama ◽  
Naoyuki Kubota
Keyword(s):  
System Integration ◽  
Industrial Sector ◽  
Human Robot Interaction ◽  
Service Robots ◽  
Smart Devices ◽  
Smart Device ◽  
User Centered Design ◽  
Human Communication ◽  
Robot Interaction ◽  
Development Platform

This paper presents a robot partner development platform based on smart devices. Humans communicate with others based on the basic motivations of human cooperation and have communicative motives based on social attributes. Understanding and applying these communicative motives become important in the development of socially-embedded robot partners. Therefore, it is becoming more important to develop robots that can be applied according to needs while taking these human communication elements into consideration. The role of a robot partner is more important in not only on the industrial sector but also in households. However, it seems that it will take time to disseminate robots. In the field of service robots, the development of robots according to various needs is important and the system integration of hardware and software becomes crucial. Therefore, in this paper, we propose a robot partner development platform for human-robot interaction. Firstly, we propose a modularized architecture of robot partners using a smart device to realize a flexible update based on the re-usability of hardware and software modules. In addition, we show examples of implementing a robot system using the proposed architecture. Next, we focus on the development of various robots using the modular robot partner system. Finally, we discuss the effectiveness of the proposed robot partner system through social implementation and experiments.

scholarly journals Heterogeneous Data Integration Architecture-Challenging Integration Issues

2015 ◽  
Vol 15 (1) ◽  
pp. 7 ◽  
Author(s):  
Michal Chromiak ◽  
Marcin Grabowiecki
Keyword(s):  
Data Integration ◽  
Data Processing ◽  
System Integration ◽  
Current Trend ◽  
Heterogeneous Data ◽  
Heterogeneous Data Integration ◽  
Design Concepts ◽  
Integration Architecture ◽  
Efficient Data ◽  
Processing Engine

As of today, most of the data processing systems have to deal with a large amount of data originated from numerous sources. Data sources almost always differ regarding its purpose of existence. Thus model, data processing engine and technology differ intensely. Due to current trend for systems fusion there is a growing demand for data to be present in a common way regardless of its legacy. Many systems have been devised as a response to such integration needs. However, the present data integration systems mostly are dedicated solutions that bring constraints and issues when considered in general. In this paper we will focus on the present solutions for data integration, their flaws originating from their architecture or design concepts and present an abstract and general approach that could be introduced as an response to existing issues. The system integration is considered out of scope for this paper, we will focus particularly on efficient data integration.

scholarly journals Extract Executable Action Sequences from Natural Language Instructions Based on DQN for Medical Service Robots

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Fengda Zhao ◽  
Zhikai Yang ◽  
Xianshan Li ◽  
Dingding Guo ◽  
Haitao Li
Keyword(s):  
Natural Language ◽  
Short Term Memory ◽  
Average Length ◽  
Service Robots ◽  
Short Term ◽  
Medical Robots ◽  
Agent Based ◽  
Action Sequences ◽  
Long Short Term Memory ◽  
Better Than

The emergence and popularization of medical robots bring great convenience to doctors in treating patients. The core of medical robots is the interaction and cooperation between doctors and robots, so it is crucial to design a simple and stable human-robots interaction system for medical robots. Language is the most convenient way for people to communicate with each other, so in this paper, a DQN agent based on long-short term memory (LSTM) and attention mechanism is proposed to enable the robots to extract executable action sequences from doctors’ natural language instructions. For this, our agent should be able to complete two related tasks: 1) extracting action names from instructions. 2) extracting action arguments according to the extracted action names. We evaluate our agent on three datasets composed of texts with an average length of 49.95, 209.34, 417.17 words respectively. The results show that our agent can perform better than similar agents. And our agent has a better ability to handle long texts than previous works.

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