Myung Chan Roh

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.

Autonomous navigation of transport robot in the urban environment

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.

Autonomous driving through Curb detection and tracking

This paper presents a strategy to detect and track the curb which means a stone separates road and non-road using a LRF (Laser Range Finder) with particle filter. Our approach to find the position of curb involves two stages. In first stage, Curb detection through curb geometric shape recognize and detect the position of the curbs in laser scanner data. A second stage processes is the curb estimation and tracking using particle filter with laser scanner. Experiments are carried out at the autonomous vehicle in real structured road, and results show the promising performance of the presented method.