In this paper, we introduce an internal pipeline exploration of an in-pipe robot, based on the landmark recognition system. The fittings of pipelines such as elbows and branches are used as the landmarks. The robot recognizes the landmarks with a vision system by using the shadows of the elements, which are generated by the specially designed illuminator on the robot. By using a simple image-processing, the robot can easily detect and distinguish these landmarks while recognizing the direction of the pipeline path. Simultaneously, all information for exploration is continuously recorded and used to reconstruct the map of the pipelines. The effectiveness of the proposed method is verified by real experiments using the in-pipe robot MRINSPECT V for moving inside of the miniature urban 8-inch gas pipeline structure.

Recently researches on the window cleaning robot are being conducted actively. Moving mechanisms of these window cleaning robots are divided into two categories, which are towed type and walking type. Towed type is focused on fast cleaning on the flat surface of building and walking type has priority on cleaning task on relatively complex surface with overcoming obstacles. Currently commercialized towed type window cleaning robot has weakness that it is hard to adhere closely with the wall and easy to be affected by wind. In case of walking type it has the problem that the position errors are continuously accumulated during motion. In this paper, we propose new towed and walking type mechanism which can compensate previous weaknesses. After that we estimate the performance of each proposed mechanism by simulation.

The docking and recharging system for a mobile robot must guarantee the ability of the mobile robot to perform its tasks continuously without human intervention. In this paper, two docking mechanisms are proposed with localization error-compensation capability for the auto recharging system. Friction forces or magnetic forces are used between the docking parts of the docking module and those of the docking station. In addition, an auto recharging system is developed to control the power. Since the system is modularized, it can easily be adapted to other robots.