• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.9-15
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• 2016

Source localization has developed in various fields of signal processing including radar, sonar, and wireless communication, etc. Source localization can be found by estimating the time difference of arrival between the each of sensors. Several methods like the NLS(Nonlinear Least Square) cost function have been proposed in order to improve the performance of time delay estimation. In this paper, we propose a clustering method using the four sensors with the same aperture as previous methods of using the three sensors. Clustering method can be improved the source localization performance by grouping similar estimated values. The performance of source localization using clustering method is evaluated by Monte Carlo simulation.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.134-141
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• 2014

Mobile robots use various sensors for navigation such as wheel encoder, vision sensor, sonar, and laser sensors. Dead reckoning is used with wheel encoder, resulting in the accumulation of positioning errors. For that reason wheel encoder can not be used alone. Too much information of vision sensors leads to an increase in the number of features and complexity of perception scheme. Also Sonar sensor is not suitable for positioning because of its poor accuracy. On the other hand, laser sensor provides accurate distance information relatively. In this paper we propose to extract the angular information from the distance information of laser range finder and use the Kalman filter that match the heading and distance of the laser range finder and those of wheel encoder. For laser scanner with one feature point error may increase much when the feature point is variant or jumping to a new feature point. To solve the problem, we propose to use two feature points and show that the positioning error can be reduced much.

• Journal of Construction Engineering and Project Management
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• v.6 no.2
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• pp.30-39
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• 2016

This research presents the development of a self-governing mobile robot navigation system for indoor construction applications. This self-governing robot navigation system integrated robot control units, various positioning techniques including a dead-reckoning system, a UWB platform and motion sensors, with a BIM path planner solution. Various algorithms and error correction methods have been tested for all the employed sensors and other components to improve the positioning and navigation capability of the system. The research demonstrated that the path planner utilizing a BIM model as a navigation site map could effectively extract an efficient path for the robot, and could be executed in a real-time application for construction environments. Several navigation strategies with a mobile robot were tested with various combinations of localization sensors including wheel encoders, sonar/infrared/thermal proximity sensors, motion sensors, a digital compass, and UWB. The system successfully demonstrated the ability to plan an efficient path for robot's movement and properly navigate through the planned path to reach the specified destination in a complex indoor construction site. The findings can be adopted to several potential construction or manufacturing applications such as robotic material delivery, inspection, and onsite security.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.151-169
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• 2014

We propose a new technique for autonomous navigation and travelling of mobile robot based on ultrasonic sensors through the narrow labyrinth that leave only distance of a few centimeters on each side between the guides and the robot. In our current implementation the ultrasonic sensor system fires at a rate of 100 ms, that is, each of the 8 sensors fires once during each 100 ms interval. This is a very good firing rate, implemented here for optimal performance. This paper presents an extensively tested and verified solution to the problem of obstacle avoidance. Our solution is based on the optimal placement of ultrasonic sensors at strategic locations around the robot. Both the sensor location and the associated navigation algorithm are defined in such a way that only the accurate radial sonar data is used for accurate travelling.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.12-16
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• 2001

To analyze the performance of array shape estimation techniques using auxiliary sensors, the appropriate number and the positions of auxiliary sensors are investigated. Also, a post-processing technique based on spline interpolation is proposed to improve the performance of array shape estimation. The simulation results showed that when auxiliary sensors are arranged uniformly, the performance of shape estimation is better than other arrangements of auxiliary sensors. Also, the proposed post-processing technique improved the performance of the existing shape estimation method, such as Kalman filter method.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.271-274
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• 1998

Ultrasonic sensors are becoming indispensable components in every sector of automation equipments due to many advantages. But the main purposes of the noncontact sensing device are rather narrowly confined within object detection and distance measurement. To widen the realm of the applications to object recognition, ultrasonic sensors need to improve the recognition resolution to a certain amount. To resolve the problem of spatial resolution restriction, an increased number of the sensors in the forms of a linear array or 2-dimensional array of the sensor has been used. Also better resolution has been obtained by shifting the array in several steps using mechanical actuators. For an object recognition using ultrasonic sensors, measurements of distance, shift, oblique angle in certain ranges should be obtained. But a little attention has been paid to the measurement of angles. In this paper we propose a practical method for an object angular value detection in addition to distance measurement in ultrasonic sensor array system with little additional hardware burden. Using the established measurement look-up table for the variations of distance, shift, angle and transmitter voltages for each sensor characteristics, a set of different return echo signals for adjacent receivers are processed to provide enhanced angular value reading for an object.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.499-505
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• 2018

Time delay estimation between two acoustic sensors is widely used in room acoustics and sonar for target position estimation, tracking and synchronization. A cross-correlation based method is representative for the time delay estimation. However, this method does not have enough consideration for the noise added to the receiving acoustic sensors. This paper proposes a new time delay estimation method considering the added noise on the receiver acoustic sensors. From comparing with the existing GCC (Generalized Cross Correlation) method, and adaptive eigen decomposition method, we show that the proposed method outperforms other methods for a colored signal source in the white Gaussian noise condition.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.119-124
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• 1993

This paper describes a method of producing maps of an indoor environment with an autonomous mobile robot equipped with sonar array. This method uses the certainty grid suitable for accommodation of inaccurate sensor data and real-time navigation. Each grid contains a certainty vale that indicates the measure of confidence that an obstacle exists within th grid area. The scheduled firing method is used to eliminate the crosstalk between ultrasonic sensors. The effectiveness of the method is verified by a series of experiments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1071-1084
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• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.495-500
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• 2002

Recently, a service robot industry outstands as an up and coming industry of the next generation. Specially, there are so many research in self-steering movement(SSM). In order to implement SSM, robot must effectively recognize all around, detect objects and make a surrounding map with sensors. So, many robots have a sonar and a infrared sensor, etc. But, in these sensors, We only know informations about between the robot and the object as well as resolution faculty is of inferior quality. In this paper, we will introduce new algorithm that recognizes objects around robot and makes a two dimension surrounding map with a omni-direction vision camera and two stereo vision cameras.