This paper describes a method for localizing wireless mobile clients in a multistory building using a public wireless Local Area Network (LAN) system. Physical location data on personal devices and mobile robots is important to information services and robot applications. Wireless mobile clients are localized in a multistory building using public wireless LAN access points placed, three-dimensionally in the building. Information on the floor number and client location is acquired probabilistically, with estimation providing a probabilistic model for localization based on sparse Bayesian learning. Results of experiments confirm the feasibility of our proposal.

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The authors have been developing a mobile robot with sensors for various services in the university campus. A prominent feature of university campus is a substantial amount of pedestrians in the outdoor environment. This feature is also typical in the shopping streets where cars are shutout. This paper proposes an application of a stochastic model for the observation and state transition for detecting mobile objects while the localization process. This model can be treated in the framework of nonlinear Kalman filter. In this paper, we implemented the detection algorithm in the offline mode. We demonstrate the experimental detection results, which validate the usefulness of the proposed algorithm.

This paper describes a method for location estimation of mobile wireless local area network (LAN) clients in multistory buildings using the strength of the received signals in a state space framework. Data pertaining to the physical positions of personal electronic devices or mobile robots are important for information services and robotic applications. We focus on integrating the estimation results with other sensor data based on a state space framework. The estimation model for location provides a variance of a mobile client's location. We integrate the estimation results and the motion results of the mobile client using a Kalman filter. The estimation model is re-initialized when the mobile client moves to another floor in the building by detecting the change in the floor number where the mobile client has moved. This is done by using the Bayesian inference. Experimental results show the feasibility of this method.

Two wheeled inverted pendulum robot which has just two driving wheels is attracted as an interesting mobile robot for several applications over the last decade. In this study, we show a framework for the mobile robot constructed by the inverted pendulum mobile robot for a project "KoRo" in our university. It is necessary to be composed by several sensors, namely sensor fusion techniques, such as a laser scanner, an USB camera, a gyro and so on. The framework of the mobile robot composed by RT middleware component with some sensors were mainly investigated.

This paper describes a method for the localization of wireless mobile clients in multistory buildings using a public wireless LAN system. The global positioning system (GPS) is used for the outdoor localization of a mobile client carried by humans or mobile robots; however, it is difficult to estimate the global position of the mobile client in multistory buildings since the GPS is not suitable for indoor localization. The proposed method uses public wireless LAN access points which are settled three-dimensionally in a building. The application of the method involves the assumption that the humans or robots carrying the mobile client move horizontally on each floor in the building. The method simultaneously estimates the position of the mobile client and its floor number. Experimental results indicate that the proposed method is feasible.

This paper proposes a method of pose (position and orientation) fitting of construction components in a construction site for automated handling based on the relation between components (parts) and their information (packets). Robots can acquire the required information of the component via the environmentattached storages, such as RFID devices. When an ID reader identifies an ID device, it should take some pose in its communication range. This fact may bring the idea of estimating the pose of a component that carries the device. In this idea, only single device identification cannot fix the pose of the component. We define the conditions of the ID reader and ID devices for the pose fitting, and propose a fitting method with at least two different identifications where two devices are not attached to the same plane or parallel planes of the component. Several examples of pose fitting show the feasibility of our idea.

In this study, a framework of fusion network with several sensors for an inverted pendulum mobile robot is investigated by developing various services as a campus robot in our university. Several devices has been equipped on the robot for sensors as detecting obstacles, walls, human body, boundary of the ground and so on. In order to implement an algorithm for safety to drive, a framework of sensor fusion network realized by RT-middleware components is explained. As one of example, we show an experimental result using the framework on the campus event.