Beom-Su Seo

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.

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

Drivable Road Detection with 3D Point Clouds Based on the MRF for Intelligent Vehicle

In this paper, a reliable road/obstacle detection with 3D point cloud for intelligent vehicle on a variety of challenging environments (undulated road and/or uphill/ downhill) is handled. For robust detection of road we propose the followings: 1) correction of 3D point cloud distorted by the motion of vehicle (high speed and heading up and down) incorporating vehicle posture information; 2) guideline for the best selection of the proper features such as gradient value, height average of neighboring node; 3) transformation of the road detection problem into a classification problem of different features; and 4) inference algorithm based on MRF with the loopy belief propagation for the area that the LIDAR does not cover. In experiments, we use a publicly available dataset as well as numerous scans acquired by the HDL-64E sensor mounted on experimental vehicle in inner city traffic scenes. The results show that the proposed method is more robust and reliable than the conventional approach based on the height value on the variety of challenging environment.

Issues and Implementation of a URC Home Service Robot

This paper reviews and discusses many issues and implementation details of an intelligent home service robot in a URC (Ubiquitous Robotic Companion) environment. In contrast to standalone service robots, URC service robots provide a variety of functions by the full utilization of network infrastructure. Many challenges are waiting to be faced in front of us-for example, the execution and coordination of services, multiple team support, session and service management, and communication protocol and its architecture, and resource management of a robot. This paper proposes solutions for the above issues and applies the solutions to a network-based home service robot called Nettoro. As an application of the proposed architecture, a pilot project launched December, 2006 is presented and the results are briefly discussed.

Design of a web services based eAI framework

This paper proposes a compact eAI framework for the integration of various types of applications deployed on different platforms on the Internet. The applications are connected and invoked to achieve a business goal by the coordination of the workflow system in the framework. For the construction of the framework, 5 sub-modules are elicited and the functions and roles of each module are defined The elicited 5 sub-modules include business process modeling tool, eAI platform, business processes transform module, UDDI connection module, and workflow system. In fhe framework, intra and inter organizational applications can be integrated together across firewalls. A full-fledged eAI solution can be constructed by gradually adding supplementary functions within this framework.

RoadPlot-DATMO: Moving object tracking and track fusion system using multiple sensors

This paper introduces the RoadPlot-DATMO, tracking objects around the vehicle using multiple sensors such as radars, 2D LiDARs, and a 3D LiDAR. It consists of the xytracker, the xyztracker, and the fusion; the xytracker tracks moving objects with multiple 2D LiDARs, the xyztracker perceives object information in detail using a 3D LiDAR, and the fusion merges tracks from multiple trackers. It is able to detect and to track moving objects around the vehicle correctly and continuously without blind area in realtime. Also, this was tested with driverless overtaking on a highway using the autonomous vehicle, the CoPilot of the ETRI.

Fusion of multiple 2D LiDAR and RADAR for object detection and tracking in all directions

For autonomous vehicle and ADAS(Advanced Driver Assistance System), it is essential to detect and to track objects within a certain area in realtime. This paper presents the 2D tracker that fuses with four 2D LiDARs and one RADAR. It independently detects objects according to the type of sensors and represents these in the same space. It continuously associates measurements of the same object and tracks these with KF(Kalman Filter) for prediction and JPDAF(Joint Probabilistic Data Association Filter) for update. The result of our multi-sensor fusion tracker is demonstrated with a visualization tool.

The mission execution for the military robot

In order to make relatively large size robots to be worked in real fields, we need to devise the practical method for creating, allocating, and carrying out a mission based on payloads a robot has. In this paper, we introduce how to make and execute a mission for the military robot; the Dog-Horse robot.

Drivable space expansion from the ground base for complex structured roads

For driverless driving cars, it is essential to detect drivable space. It can directly apply to plan driving paths by acquiring the occupancy grid map. In addition, it can enhance object clustering by removing the ground in advance. However, in urban, not only a large number of vehicles are driving at the same time, but also roads with diverse inclinations are complicatedly connected with each other. Thus, it is challenging to extract traversable space properly from complex structured environment. For this reason, this paper proposes the real-time drivable space detection for complex urban environment by integrating the model-based segmentation and the region-based segmentation. Moreover, the proposed method utilizes point cloud from 3D LiDAR because it is effective to understand surrounding topography. It is demonstrated using hand-labeled point cloud dataset collected in various types of urban roads by estimating numerical performances and by visualizing results.

The implementation of the work management contract and the message inflow contract in the java connector architecture 1.5

The JCA(Java Connector Architecture) is the specification for integrating a J2EE application server with legacy systems such as DBMS, ERP, JMS, etc. The JCA 1.0 provides the API sets for a J2EE application server to communicate with legacy systems using three kinds of contracts. In the JCA 1.5, the new features are added including the contracts in the JCA 1.0.In this paper, I briefly introduce the JCA architecture and the basic contracts. And I discuss the implementation of the work management contracts and the message inflow contract which are the most important contracts among the new features in the JCA 1.5.