-The industry's interest in building façade maintenance is rising with the growing number of new high-rise buildings in the metropolises. The conventional method of cleaning the façade of highrise buildings relies on the use of ropes, gondolas, and the winch system involving human labor. Recently the building maintenance unit (BMU) has been developed and has been applied to building maintenance to prevent safety accidents and to ensure high work efficiency. Diverse robot systems are being applied to building maintenance globally, including in Germany, the United States, and France. In South Korea, the built-in guided robot system was developed. This paper deals with an integrated control system of builtin guided robot system to ensure consistent and stable control. This control system is considered its unique characteristics as a building façade cleaning work. The integrated control system proposed in this paper performs cleaning work in three steps: preparation, cleaning, and return to the initial position, with each module consisting of the robot system performing its task sequentially and independently at each step. In addition, the robot system makes up a network composed mainly of VMR to ensure smooth and stable communication among the different modules. The integrated control system proposed in this paper was applied to the built-in guided robot system for performance verification.

Installation work of large inner/outer wall panel glasses increases the labor load and stress of workers and causes the danger of such accidents as falling and crane overturning. To solve this problem, Gil designed the easy handling robot system which is composed of mobile system, 5-DOF manipulator system and HRI (Human-Robot Interface) device included HRC (Human-Robot Cooperation) algorithm. During glass installation work using this robot system, detecting the position of the HRI device has great influence on the work efficiency. While working there, the construction worker placed the HRI device on panel glass randomly. Also there are many factors that disturb the detecting the HRI device. In this paper describes a method for detecting the HRI device robustly. To robustly find the HRI device, in this paper, applied the RANSAC (RANdom SAmple Consensus) and LSF (Least Square Fit) algorithm. And sensor module for detect the HRI device is composed of IR (Infrared Ray) sensor and RC servo motor. The distance between the sensor module and the circle-shaped HRI device is utilized for detecting this device. In this paper, to verify the robust method, performed laboratory experiment: for detecting the HRI device randomly placed on, for finding the HRI device put with a square-shaped disturbance.