Kangwoo Lee

Context-Aware Server Framework for Network-based Service Robots

URC (ubiquitous robotic companion) is a new concept for a network-based service robot system. In this paper, we introduce CAMUS (context-aware middleware for URC systems) which is a server framework to support context-aware services for network-based robots. We discuss two major components of CAMUS: CAMUS main server and service agent manager. The communication framework is also proposed to support the communication between robots and CAMUS. We expect that CAMUS will be utilized to develop ubiquitous computing applications for network based service robot, the smart space and the personal assistant software

Designing CAMUS based Context-Awareness for Pervasive Home Environments

With the advent of pervasive computing environments, the issue related to context-aware middleware is an emerging area of research. We propose proactive services on the basis of CAMUS (context-aware middleware for URC Systems). First, this paper presents the system architecture of CAMUS. CAMUS is a middleware for providing context-aware applications with development and execution methodology. Accordingly, the applications developed by CAMUS respond in a timely fashion to contexts. Secondly, this paper illustrates the contents recommendation and control service agents with the property, operation, and task for the context-aware active services. Next, proposed active services is applied to the pervasive home environment for evaluation of our system. To do this, we implement the TV contents recommendation service agent, control service agent and context-aware task using CAMUS

Client/Server Framework for Providing Context-Aware Services to Network Based Robots

URC (ubiquitous robotic companion) is a new concept for a network-based robotic system, in which a different kinds of robots are connected to a server system to provide various robotic services. In this paper, we introduce the client/server framework to provide context-aware services to network-based robots. We call the framework as CAMUS (context-aware middleware for URC systems). The CAMUS is mainly composed of three parts: service agent managers, CAMUS server and planet. The service agent manager is the robot-side framework to send robots sensing data to the CAMUS server and receive control commands from the CAMUS server. The CAMUS server is the server-side framework to manage information from service agent managers, generate and disseminate appropriate events according to the context changes, and finally execute server-based robot tasks. The planet is the communication framework between service agent managers and the CAMUS server. This paper also discusses the implementation of the URC field test applications.

Introduction to system architecture for a robotic computer

Recently, there have been a variety of products and research prototypes to introducé a new type of computing device in our living environment. Robots have great potential to be used as a new type of devices. In this paper, we introducé our on-going development of the robotic computer that naturally interacts with users, understands the current situation of users and environments, and proactively provides users with services. The proposed robotic computer consists of a control unit and an agent unit. The control unit, which is a remote processing server connected to the host server of the smart environment, provides memory (high-level information) and processing (computing resources) capabilities to the agent unit. The agent unit is a portable device that is wirelessly connected to the control unit, and interacts with users and physical objects. We describe the system architecture and the implementation of a proof-of-concept prototype of the proposed robotic computer.

Convergence of context-awareness and augmented reality for ubiquitous services and immersive interactions

Computing paradigm is moving toward context-aware and ubiquitous computing in which devices, software agents, and services are all expected to seamlessly integrate and cooperate in support of human objectives. Augmented reality (AR) can naturally complement ubiquitous computing by providing an intuitive and collaborative interface to a three-dimensional information space embedded within physical reality. This paper presents a framework and its applications for the convergence of context-awareness and augmented reality, which can support a rich set of ubiquitous services and immersive interactions. The framework provides a common data model for different types of context information from external sensors, applications and users. It also offers the software framework to acquire, interpret and disseminate context information. Further, it utilizes augmented reality for providing immersive interactions by embedding virtual models onto physical models, which realizes bi-augmentation between physical and virtual spaces.

Integration framework for interoperability of distributed and heterogeneous robot middlewares

This paper describes the ongoing development of a software framework for supporting interoperability and integration among heterogeneous network-based robotic development frameworks. We studied two of network based robotic software development frameworks named CAMUS framework and RT-middleware. The CAMUS (context-aware middleware for URC systems) is a middleware developed by Electronics and Telecommunications Research Institute (ETRI), in Korea, based on the URC (ubiquitous robot companion) concept for developing network based robotic systems. On the other hand, The RT-middlware was developed by Agency of Industrial Science and Technology(AIST), in Japan, to promote applications of robot technology (RT) in various fields. The proposed framework supports interoperability and interconnection among modularized software named RT-components (RTC) in the context of RT-middleware and service agents (SA) in the context of CAMUS framework. We also implemented and tested some components based on the proposed approach.

Smart memo service design for augmented smart space

In this paper, we present our approach for developing a smart space environment. The system is fundamentally designed for adaptive information augmentation within a physical space with a projector and depth cameras, and various technologies are converged including spatial relations and contextual semantic knowledge management, user tracking and facial recognition, etc. The system design is focused on the smart memo service scenario, where messages bound to certain people or objects can be displayed on nearby surfaces.

A shared interactive smart table based on camera-projector systems

One of the key challenges of remote sharing systems based on camera-projector pairs is the visual echo problem. However, existing visual echo cancellation schemes are either too theoretical or hardware-dependent to deploy for common use in arbitrary systems. Therefore, we present a simple and practical visual echo cancellation scheme. Experimental results shows that our system exhibits performance no less than 10 fps on exchanging non-echo images of 640 × 480 size in a full-duplex mode.

Autonomous behavior control subsystem for robotic computer

Successful development of a robotic computer as a mediator in smart environments requires providing a certain level of behavior autonomy to the robot and a capability to adapt its behavior in long-term interaction with the users. We attempt to identify core autonomy-related functionalities and describe the design and implementation of an autonomous behavior control subsystem that provides them. The choice of dual-level behavior model with both rules and connectionist reinforcement learning is motivated by the desire to provide convenient specification of initial behaviors as well as efficient behavior adaptation capability. We present the results of two test scenarios illustrating basic use of the newly provided functionality.

Ontology-based context and preference model for personal service robot

To enhance the usability of personal service robots, some level of autonomous behaviours are required in the process of service provision so that the users do not need to intervene in every step of the service execution process. Such automation can be achieved by utilising contextual knowledge and user preferences. In this paper, we present an ontology-based context and preference model on the basis of our robotic device. Our context model represents the environmental context information and derives higher-level contextual knowledge via rule-based reasoning. In addition, each users preference knowledge is also modelled in our knowledge base, describing the different preferences on services, contents and device settings based on the current context. Following the description of our knowledge model, we discuss its integration with our robotic agent system, and it is concluded with some experimental results.