Youngjin Park

Sound direction estimation using an artificial ear for robots

We propose a novel design of an artificial robot ear for sound direction estimation using two measured outputs only. The spectral features in the interaural transfer functions (ITFs) of the proposed artificial ears are distinctive and move monotonically according to the sound direction. Thus, these features provide effective sound cues to estimate sound direction using the measured two output signals. Bilateral asymmetry of microphone positions can enhance the estimation performance even in the median plane where interaural differences vanish. We propose a localization method to estimate the lateral and vertical angles simultaneously. The lateral angle is estimated using interaural time difference and Woodworth and Schlosbergs formula, and the front-back discrimination is achieved by finding the spectral features in the ITF estimated from two measured outputs. The vertical angle of a sound source in the frontal region is estimated by comparing the spectral features in the estimated ITF with those in the database built in an anechoic chamber. The feasibility of the designed artificial ear and the estimation method were verified in a real environment. In the experiment, it was shown that both the front-back discrimination and the sound direction estimation in the frontal region can be achieved with reasonable accuracy. Thus, we expect that robots with the proposed artificial ear can estimate the direction of speaker from two output signals only.

Spatially Mapped GCC Function Analysis for Multiple Source and Source Localization Method

A variety of methods for sound source localization have been developed and applied to several applications such as noise detection system, surveillance system, teleconference system, robot auditory system and so on. In the previous work, we proposed the sound source localization using the spatially mapped GCC functions based on TDOA for robot auditory system. Performance of the proposed one for the noise effect and estimation resolution was verified with the real environmental experiment under the single source assumption. However, since multi-talker case is general in human-robot interaction, multiple source localization approaches are necessary. In this paper, the proposed localization method under the single source assumption is modified to be suitable for multiple source localization. When there are two sources which are correlated, the spatially mapped GCC function for localization has three peaks at the real source locations and imaginary source location. However if two sources are uncorrelated, that has only two peaks at the real source positions. Using these characteristics, we modify the proposed localization method for the multiple source cases. Experiments with human speeches in the real environment are carried out to evaluate the performance of the proposed method for multiple source localization. In the experiments, mean value of estimation error is about and percentage of multiple source localization is about 62% on average.

Newly Designed HRTF Measurement System and its Analysis

When we render 3D sound images using headphones or speakers, the main key of this technology is the Head-related transfer function (HRTF) database. Even though there are various HRTF databases, they have some drawbacks such as detrimental effects caused by imperfect measuring environment and insufficient measurement points. Moreover there is no database with Korean subjects. We are planning to develop the HRTF database for Korean. As a first step to establish the HRTF database aimed at Korean, the new HRTF measurement system with minimized aforementioned drawbacks is designed. In this paper, the newly designed HRTF measurement system is introduced and the overall effects caused by the diffraction of the apparatus, especially the headrest and backrest of the chair, are analyzed. The backrest of the chair does not distort the HRTFs significantly while the headrest makes significant distortion on the HRTFs and it could have significant effects on directional perception. We determined acceptable head rotation angle and head position of the subject for accurate HRTF measurement based on the experiments with B&K HATS. We conclude that the 3 degrees of the head rotation and the 1.5cm front/back/left/right shift of the head do not distort the HRTFs significantly.

Design Observable Model of Direct Drive Motor for Air Gap Estimation when Input Disturbance is Impulse signal

Observable mathematical model of DDM (Direct Dirve Motor) was suggested. The motor that operates the object system directly is called DDM. DDM has many strong points, however, it has a significant disadvantage, that it is more sensitive to the external force than the motor with reduction gear. In other word, if the force is applied, air gap of the motor can be perturbed. This causes not only difficulty in motor control but also even more serious problem, such as the breakdown of motor. However, if the air gap variation can be estimated, it can help prevent these problems. DDM should be modeled to estimate the air gap variation. The type of researched DDM is PMSM (Permanent Magnet Synchronous Motor) and precedent model of PMSM includes only characteristics of electro-magnetic system and rotational motion. However, suggested model should also include characteristics of translational motion of rotor to estimate the air gap variation. Also, this model should satisfy observability condition, because state observer is designed based on this model.

Attitude Estimation for the Biped Robot with Vision and Gyro Sensor Fusion

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.