Yong-beom Lee

Application of Electronic Compass for Mobile Robot in an Indoor Environment

This paper presents a novel approach to electronic compassing for robot in an indoor environment. Operation of compass (magnetometer) is assumed on a mobile robot that is capable to traverse a complete circular path. The electronic compass is used to estimate a robot absolute heading with respect to the magnetic North. This is only compass approach where an evaluation of quality of calibration and magnetic environment is important as much as calibration itself. In this method, compass is able to detect the external magnetic interference and estimate it numerically. The approach also relates to automatic calibration and requires one full 360-degree rotation and multiple points for further analysis. This enhanced calibration procedure is performed in the magnetic field domain and implemented using a non-iterative algebraic technique. The quality of calibration is a function of input data goodness and how successful is the fitting procedure. The magnetic environment evaluation is performed by the distortion factor that is calculated at the end of calibration and helps to estimate quantitatively local external magnetic distortions and their influence on a heading measurement. The validity of this approach has been verified experimentally by using robot with electronic compass.

Lenticular stereoscopic imaging and displaying techniques with no special glasses

Autostereoscopic 3-D imaging and display system is implemented on the notebook 486 DxII PC with TFT active matrix LCD display module and accompanying lenticular sheet lens. An image processing board (e.g. Targa Plus which is commercially available) is used to capture and display the image. Display experiments for still images and animating graphics images were very promising and satisfactory. Measured depth perception is about 100 mm on a notebook PC LCD display unit. The compact design of lens-plate and TFT LCD display module would be appropriate for 3-D game machines, stereoscopic TV system on multimedia PC.

Simultaneous Geometric and Radiometric Adaptation to Dynamic Surfaces With a Mobile Projector-Camera System

Existing geometric and radiometric compensation methods for direct-projected augmented reality focus on static projection surfaces rather than dynamic surfaces (with varying geometry in time). We aim at providing an effective framework for projecting a sequence of augmented reality images onto dynamic surfaces without geometric and radiometric distortion. We present our design of a special pattern image for simultaneous geometric and radiometric compensation and evaluate two different techniques for embedding the pattern image into augmented reality images. The validity of the proposed method is examined through a variety of experiments with a mobile projector-camera system.

Constrained Kalman Filter for Mobile Robot Localization with Gyroscope

The odometry information used in localization can be quite erroneous when the robot follows the curved path or suffers from slippage. Thus the use of the low-cost gyroscope to compensate for an angular error is considered by many researchers. Conventional Kalman filtering methods that fuse the odometry with the gyroscope may produce infeasible solution because the robot parameters are estimated regardless of their physical constraints. In this paper, we propose a constrained Kalman filtering method that applies general constrained optimization technique to the estimation of the robot parameters. The state observability is improved by the additional state variables and the accuracy is also improved by the nonapproximated Kalman filter design. Experimental results show the proposed method effectively compensates for the odometry error and yields feasible parameter estimation at the same time

Real-time audio-visual localization of user using microphone array and vision camera

In home environments, demands for a robot to serve a user are on the increase, such as cleaning rooms, bringing something to the user, and so on. To achieve these tasks, it is essential for developing a natural way of human-robot interaction (HRI). One of the most natural ways is that the robot approaches the user to do some tasks after recognizing the users call and localizing its position. In this case, user localization becomes a key technology. In this paper, we propose a novel audio visual user localization system. It consists of a microphone array with eight sensors and a video camera. Estimating calling direction is achieved by the spectral subtraction of the spatial spectra. In particular, a novel beam forming method is proposed to suppress the nonstationary audio noises where they always occur in a real world. Furthermore, a robust method for face detection is proposed to double check the user based on an Adaboost classifier. It is improved to reduce the false alarms remarkably through a new postprocessing on face candidates. Successful results in a real home environment show its efficacy and feasibility. The implementation issues, limitations, and their possible solutions are also discussed.

Detecting and tracking people by mobile robot using structured light range sensor

An effective human-robot interaction is essential for wide penetration of mobile home robots into the market. The ability to track human in the home environment is one of fundamental functions of home robots. In this paper, we introduce a prototype of Samsung home robot (SHR) developed by Samsung Advanced Institute of Technology (SAIT) and present a scheme of tracking user movement utilizing a structured light range sensor. The structured light range sensor is considered to be cost-effective and robust for a wide range of environment; however, its low resolution of range data tends to extract wrong features for the human tracking, such as table legs, trash cans, door-edges, etc. To compromise this weakness, we have developed an algorithm that excludes those features that do not come from human legs. Efficacy and robustness of this proposed system were examined through experiments in the real home environment.

Adaptive Cross-Channel Interference Cancellation on Blind Source Separation Outputs

Despite an abundance of research outcomes of blind source separation (BSS) in many types of simulated environments, their performances are still not satisfiable to apply to the real environments. The major obstacle may seem the finite filter length of the assumed mixing model and the nonlinear sensor noises. This paper presents a two-step speech enhancement method with stereo microphone inputs. The first step performs a frequency-domain BSS algorithm with no prior knowledge of the mixed source signals and generates stereo outputs. The second step further removes the remaining cross-channel interference by a spectral cancellation approach using a probabilistic source absence/presence detection technique. The desired primary source is detected every frame of the signal, and the secondary source is estimated in the powerspectral domain using the other BSS output as a reference interference source. Then the secondary source is subtracted to remove the cross-channel interference. Our experimental results show good separation enhancement performances on the real recordings of speech and music signals compared to the conventional BSS methods.

Split and merge approach for detecting multiple planes in a depth image

We propose a novel method for detecting multiple planar structures in a scene from a depth image, and estimating their parametric models in real time. To realize this goal we split an entire depth image into small patches. Initially, we assume that all patches are on the planar structure and estimate their parametric models using least square fitting. We select patches where our assumption is valid and the selected planar patches are iteratively merged and refined in case that they are in the same planar structure. The qualitative and quantitative experiments shows that the proposed method has clear benefits in terms of accuracy and processing time.

Mobile pointing and input system using active marker

We present a mobile pointing and input system for mobile phones with minimal hardware parts that allows users who wear an eyeglass display to view and interact with a large virtual image. To use the mobile phone as a pointing and input device, a fiducial marker-based tracking system developed for augmented reality is adapted for our system. The brightness and shape of active marker could be changed according to the state of operating environment and/or the users intentions in order to increase the detection rate of the marker.

Pose estimation of a depth camera using plane features

We present a novel method for pose estimation of a depth camera through plane features. Since conventional features for color images, mainly points and lines, are not applicable to a depth image, we propose a new type of feature utilizing planar structures in a scene. To measure the accuracy of our method, we generated a synthetic scene and calculated a position error between an estimated location and its ground truth. We also applied our method to the real world scene captured by a depth camera verifying practical usage.