The lighthouse localization system has recently been developed and used for localization in virtual reality (VR). Not only for VR but also for a general indoor positioning systems (IPSs) it has several advantages over existing methods, including low cost, wide detection area, and easy setup. Here, we adopt the stereo configuration of a lighthouse for improved sensing performance and propose a novel calibration method for stereo configuration. For the stereo calibration, the exact positions of sufficient corresponding points in two sensor coordinates need to be determined. A printed checkerboard is widely used for stereo camera systems because it is easy to construct and its accuracy is guaranteed owing to its printing accuracy. However, in the case of the lighthouse system, it is very difficult or impossible to construct a highly accurate calibration board similar to the checkerboard mainly because of manufacturing errors. In this study, we use a receiver sensor and a two-axis linear stage equipped with micrometers. By moving predetermined distances along the x and y directions on the linear stage, we can obtain multiple-point information with high accuracy, which can then be used for the stereo calibration of two lighthouses. In this paper, the calibration and pose estimation procedures are described in detail, and the pose estimation result of the perspective-n-points method is compared with that of the triangulation method. Finally, the pose estimation accuracy of the proposed system is compared with that of a commercial system that is widely used for highly accurate medical applications.

Although non-invasive brain stimulation techniques do not involve surgical procedures, the challenge remains in correctly locating the stimulator from outside the head. There is a limit to which one can manually and precisely position and orient the stimulator or repeatedly move the stimulator around the same position. Therefore, in this study, we developed a serial robot with 6 degrees-of-freedom to move the stimulator and a neuro-navigation system to determine the stimulus point from looking at the shape of the subject’s brain. The proposed robot applied a spherical mechanism while considering the safety of the subject, and the workspace of the robot was designed considering the shape of the human head. Position-based visual servoing was applied to compensate for unexpected movements during subject stimulation. We also developed a neuro-navigation system that allows us visually to check the focus of the stimulator and the human brain at the same time and command the robot to the desired point. To verify the system performance, we first performed repeatability and motion compensation experiments of the robot and then evaluated the repeated biosignal response experiments through transcranial magnetic stimulation, a representative technique of non-invasive brain stimulation.