Object Surface Recognition Based on Standing Waves in Acoustic Signals.

This paper proposes the use of the standing waves created by the interference between transmitted and reflected acoustic signals to recognize the size and the shape of a target object. This study shows that the profile of the distance spectrum generated by the interference encodes not only the distance to the target, but also the distance to the edges of the target surface. To recognize the extent of the surface, a high-resolution distance spectrum is proposed, and a method to estimate the points on the edges by incorporating observations from multiple measurement is introduced. Numerical simulations validated the approach and showed that the method worked even in the presence of noise. Experimental results are also shown to verify that the method works in a real environment.

Estimation of a Human-Maneuvered Target Incorporating Human Intention.

This paper presents a new approach for estimating the motion state of a target that is maneuvered by an unknown human from observations. To improve the estimation accuracy, the proposed approach associates the recurring motion behaviors with human intentions, and models the association as an intention-pattern model. The human intentions relate to labels of continuous states; the motion patterns characterize the change of continuous states. In the preprocessing, an Interacting Multiple Model (IMM) estimation technique is used to infer the intentions and extract motions, which eventually construct the intention-pattern model. Once the intention-pattern model has been constructed, the proposed approach incorporate the intention-pattern model to estimation using any state estimator including Kalman filter. The proposed approach not only estimates the mean using the human intention more accurately but also updates the covariance using the human intention more precisely. The performance of the proposed approach was investigated through the estimation of a human-maneuvered multirotor. The result of the application has first indicated the effectiveness of the proposed approach for constructing the intention-pattern model. The ability of the proposed approach in state estimation over the conventional technique without intention incorporation has then been demonstrated.

Design of UAV-Embedded Microphone Array System for Sound Source Localization in Outdoor Environments.

In search and rescue activities, unmanned aerial vehicles (UAV) should exploit sound information to compensate for poor visual information. This paper describes the design and implementation of a UAV-embedded microphone array system for sound source localization in outdoor environments. Four critical development problems included water-resistance of the microphone array, efficiency in assembling, reliability of wireless communication, and sufficiency of visualization tools for operators. To solve these problems, we developed a spherical microphone array system (SMAS) consisting of a microphone array, a stable wireless network communication system, and intuitive visualization tools. The performance of SMAS was evaluated with simulated data and a demonstration in the field. Results confirmed that the SMAS provides highly accurate localization, water resistance, prompt assembly, stable wireless communication, and intuitive information for observers and operators.