For the underwater localization, acoustic sensor systems are widely used due to greater penetration properties of acoustic signals in underwater environments. On the other hand, the good penetration property causes multipath and interference effects in structured environment too. To overcome this demerit, a localization method using the attenuation of electro-magnetic(EM) waves was proposed in several literatures, in which distance estimation and 2D-localization experiments show remarkable results. However, in 3D-localization application, the estimation difficulties increase due to the nonuniform (doughnut like) radiation pattern of an omni-directional antenna related to the depth direction. For solving this problem, we added a depth sensor for improving underwater 3D-localization with the EM wave method. A micro scale pressure sensor is located in the mobile node antenna, and the depth data from the pressure sensor is calibrated by the curve fitting algorithm. We adapted the depth(z) data to 3D EM wave pattern model for the error reduction of the localization. Finally, some experiments were executed for 3D localization with the fast calculation and less errors.

An electric motor is the one of the most important parts in robot systems, which mainly drives the wheel of mobile robots or the joint of manipulators. According to the requirement of motor performance, the controller type and parameters vary. For the wheel driving motors, a speed tracking controller is used, while a position tracking controller is required for the joint driving motors. Moreover, if the mechanical parameters are changed or a different motor is used, we might have to tune again the controller parameters. However, for the beginners who are not familiar about the controller design, it is hard to design pertinently. In this paper, we develop a nominal robust controller model for the velocity tracking of wheel driving motors and the position tracking of joint driving motors based on the disturbance observer (DOB) which can reject disturbances, modeling errors, and dynamic parameter variations, and propose the methodology for the determining the least control parameters. The proposed control system enables the beginners to easily construct a controller for the newly designed robot system. The purpose of this paper is not to develop a new controller theory, but to increase the user-friendliness. Finally, simulation and experimental verification have performed through the actual wheel and joint driving motors.