M. Hashimoto

Bio: M. Hashimoto is an academic researcher from Hiroshima City University. The author has contributed to research in topics: Dead reckoning & Azimuth. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Optical azimuth sensor for indoor mobile robot navigation

Abstract: A new type of azimuth angular sensor for an indoor mobile robot navigation is developed. This is a kind of optical sensors using infrared linear polarization. Since an angle is measured without contact, it is applicable to the navigation of an autonomous mobile robot. In the indoor environment, the navigation system by using GPS cannot be used. In dead reckoning, the accumulation of measurement error occurs a serious problem. If we use this sensor, we can measure a position only by installing one landmark all over the working space. We can acquire simultaneously not only the distance from a landmark but an angle of direction. Like a gyroscope or a geomagnetism sensor, the large drift depending on environment or time does not occur by this sensor. We make a prototype of the sensor based on this technique and conduct the measurement experiment. The accuracy of azimuth angle error is about 4% and the radial error is 93(mm) at 3(m) distance from the landmark.

Indoor IR azimuth sensor using a linear polarizer

Abstract: We propose an Infrared-Ray (IR) type azimuth sensor system for use in indoor environments. The feature of this sensor is an adequate conic-shaped linear polarizer film. Because of the drift in the sensor, azimuth information provided by the angular velocity sensor (gyroscope) is unreliable. It is not currently possible, in virtually any indoor environment like an office or factory, to use geomagnetism to detect the existence of iron-based furniture or reinforced concrete. Our sensor system can recognize a position measured from the non-drift azimuth information based on the installation of only one landmark. We created a prototype of the sensor based on this concept and discuss the sensing properties, as indicated by experimental results.

Opportunistic Doppler-Only Indoor Localization Via Passive Radar

Abstract: Indoor localization is a vital ingredient for many e-Healthcare and Ambient Assisted Living (AAL) applications. However, accurate, low power and user acceptable solutions remain elusive. In this paper, we present a novel opportunistic system which estimates the localization information based only on the Doppler information from the user. The Doppler information is collected using the passive radar technique that deploys the RF energy transfer signal which originally intended only to deliver energy to home IoT devices. A low complexity Extended Kalman Filter (EKF) is also proposed to predict and track the user's location. A real-time system has been built based on the software defined radio (SDR) platform to verify the proposed methodology. Experimental results indicate that the proposed concepts can be used for indoor localization with a high degree of accuracy.