Young-Jo Cho

The PEIS-Ecology project: Vision and results

The vision of an ecology of physically embedded intelligent systems, or PEIS-Ecology, combines insights from the fields of autonomous robotics and ambient intelligence to provide a new approach to building robotic systems in the service of people. In this paper, we present this vision, and we report the results of a four-year collaborative research project between Sweden and Korea aimed at the concrete realization of this vision.We focus in particular on three results: a robotic middleware able to cope with highly heterogeneous systems; a technique for autonomous self-configuration and reconfiguration; and a study of the problem of sharing information of both physical and digital nature.

A stable target-tracking control for unicycle mobile robots

This paper deals with target tracking control of unicycle type mobile robots. Target tracking function is essential for autonomous robots such as guide robots, security guard robots, etc. In the field of mobile robot control, many control schemes for posture stabilization and trajectory tracking problem have been proposed. Target tracking control, however, cannot be achieved using these kinds of control laws. Therefore, a new global asymptotic stable controller for this problem is designed using the backstepping method. The stability of the system is proved using the Lyapunov function. Various simulation results validate the performance and theoretical analysis.

CAMUS: a middleware supporting context-aware services for network-based robots

A URC (ubiquitous robotic companion) is a concept for a network-based service robot. It allows the service robot to extend its functions and services by utilizing external sensor networks and remote computing servers. It also provides the robots services at any time and any place. The URC requires not only the hardware infrastructure such as ubiquitous networks or sensor networks and high-performance computing servers but also the software infrastructure which resides above the hardware infrastructure. In this paper, authors introduce the CAMUS (context-aware middleware for URC system) as a part of the software infrastructure, which is a system middleware to support context-aware services for network-based robots. The CAMUS is based on the CORBA technology. It provides the common data model for different types of context information from external sensors, applications and users in the environment. It also offers the software framework to acquire, interpret and disseminate context information. PLUE (Programming Language for Ubiquitous Environment) is proposed to describe context-aware services for robots.

PEIS Ecology: integrating robots into smart environments

We introduce the concept of ecology of physically embedded intelligent systems, or PEIS-ecology. This is a network of heterogeneous robotic devices (PEIS) pervasively embedded in the environment. A PEIS can be as simple as a toaster and as complex as a humanoid robot. PEIS can exchange information at different levels of abstraction, and share both physical and virtual functionalities to perform complex tasks. By putting together insights from the fields of autonomous robotics and of ambient intelligence, the PEIS-ecology approach explores a new road to building assistive, personal, and service robots. In this paper, we discuss this concept, describe a first realization of it, and show an implemented use-case scenario

Service-oriented integration of networked robots with ubiquitous sensors and devices using the semantic Web services technology

In recent years, motivated by the emergence of ubiquitous computing technology, a new class of networked robots - ubiquitous robots - has been introduced. The URC (ubiquitous robotic companion) is our conceptual vision of ubiquitous robot which provides us with the services we need, anytime and anywhere. To realize the vision of URC, it is one of the most important requirements for the robotic systems to support seamlessness of services even though service environments changes. Specifically, it is needed for robotic systems to be interoperable with the sensors and devices in current service environments automatically, rather than statically preprogrammed for them. In this paper, we present SURF (service-oriented ubiquitous robotic framework) which enables automated integration of networked robots into ubiquitous computing environments based on the semantic Web services technology. In SURF approach, we implement interfaces for robots, networked sensors and devices as Web services. And we describe knowledge about them in OWL-S the semantic Web services ontology and register the knowledge to KB, so that a SURF agent can automatically discover required knowledge and compose a feasible service plan for the service environments. And then the agent controls robots, sensors and devices through SOAP the Web services execution protocol according to the service plan.

A robotic service framework supporting automated integration of ubiquitous sensors and devices

In recent years, due to the emergence of ubiquitous computing technology, a new class of networked robots called ubiquitous robots has been introduced. The Ubiquitous Robotic Companion (URC) is our conceptual vision of ubiquitous service robots that provides its user with the services the user needs, anytime and anywhere, in the ubiquitous computing environments. There are requirements to be met for the vision of URC. One of the essential requirements is that the robotic systems must support ubiquity of services. This means that a robot service must always be available even though there are changes in the service environment. More specifically, a robotic system needs to be interoperable with sensors and devices in its current service environments automatically, rather than statically pre-programmed for its environment. In this paper, the design and implementation of an infrastructure for URC called Ubiquitous Robotic Service Framework (URSF) is presented. URSF enables automated integration of networked robots in a ubiquitous computing environment by the use of Semantic Web Services Technologies.

Robot Localization Sensor for Development of Wireless Location Sensing Network

The localization is one of the most important issues for mobile robot. We describe a novel localization sensor suite for the development of a wireless location sensing network. The sensor suite comprises wirelessly controlled infrared landmarks and an image sensor which detects the pixel positions of infrared sources. The proposed sensor suite can operate irrespective of the illumination condition in the indoor environment. We describe the operating principles of the developed sensor suite and report the performance for mobile robot localization and navigation. The advantage of the developed sensor suite lies in its robustness and low cost to obtain localization information as well as simplicity of deployment to build a robot location sensing network. Experimental results show that the developed sensor suite outperforms the state-of-the-art localization sensor

A hybrid control architecture using a reactive sequencing strategy for mobile robot navigation

Proposes a hybrid control architecture which combines the key features of the two well-known robot control architectures; hierarchical and behavioral-based. The overall control architecture consists of three layers, i.e. the high-level planner, the middle plan executor, and the lower level monitor and behavior-based controller. In the planned task, only one behavior module is chosen by the logical coordinator in the plan executor according to the way point bin. In the exceptional situation, the central controller in the plan executor issues an additional control command to reach the planned way point. Several simulations and experiments with an autonomous mobile robot show that the proposed architecture enables the robot controller to achieve the multiple sequential goals even in a dynamic and uncertain environment.

Evolutionary role model and basic emotions of service robots originated from computers

This paper proposes an evolutionary role model for service robots with LCD touch panels such as home robots, and suggests the necessity of reestablishment of robot emotions on the basis of the new role model. The typical HRI-based peer role model is appropriate for the android, the future intelligent robot, but it failed to take into account the state of temporary robotics. In this study, a role model was proposed by allowing for the evolutionary aspects in step with the level of robot technology. Also, the feasibility of the proposed evolutionary role model was demonstrated through the experiments after parents and children interacted with a home robot that had various functions for family members. The results showed that the expected roles of home robots are user, secretary, and peer. Most of parents thought of them as human-like machines while children regarded them as peers. Home robots facial expressions depend on their roles. So, we investigated the facial expression set of home robots at work and compared them with Ekmans. We also hypothesized that if the facial expression set for a home robot at work is different from the expected one, it had a significant impact on evaluation. The results suggested the necessity of new modelling of facial expressions for home robots based on the evolutionary role model.

A robust human head detection method for human tracking

In this paper, an algorithm for human head detection over a distance exceeding 2.5 m between a camera and an object is described. This algorithm is used for the control of a robot, which has the additional limits of a moving camera, moving objects, various face orientations, and unfixed illuminations. With these circumstances, only the assumption that human head and body contours have an omega (Omega) shape is made. In order to separate the background from these omega shapes, the three basic features of gray, color and edge are used, and combined. The skin color cue is very useful when the image stream is frontal and has large face regions, and additionally has no background objects similar to the skin color. The gray cue is also important when captured faces have a lower gray level than background objects. The edge cue is helpful when captured background objects have similar gray levels and colors to those of a head, but can be discriminated by edges. Since these three methods have roughly orthogonal failure results, they serve to complement each other. The next step is a splitting method between the head and body region using the proposed method. The final step is an ellipse fitting and a head region verification algorithm. The results of this algorithm provide robustness for head rotation, illumination changing, and variable head sizes. Furthermore, it is possible to carry out real time processing