• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1040-1047
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• 2011

This paper proposes a novel method based on error back propagation neural networks to fuse laser sensor data and ultrasonic sensor data for enhancing the accuracy of mapping. For navigation of single robot, the robot has to know its initial position and accurate environment information around it. However, due to the inherent properties of sensors, each sensor has its own advantages and drawbacks. In our system, the robot equipped with seven ultrasonic sensors and a laser sensor navigates to map two different corridor environments. The experimental results show the effectiveness of the heterogeneous sensor fusion using an error backpropagation algorithm for mapping.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.411-414
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• 2000

Optical Triangulation Probes (OTPs) are widely used for their simple structure. high resolution, and long operating range. However, errors originating from speckle, inclination of the object, source power fluctuation, ambient light, and noise of the detector limit their usability. In this paper, we propose new design criteria for an error-reduced OTP. The light source module for the system consists of an incoherent light source and a multimode optical fiber for eliminating speckle and shaping a Gaussian beam Intensity profile. A diffuse-reflective white copy paper, which is attached to the object, makes the light intensity distribution on the change-coupled device(CCD). Since the peak positions of the intensity distribution are not related to the various error sources, a sub-pixel resolution signal processing algorithm that can detect the peak position makes it possible to construct an error-reduced OTP system

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.433-437
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• 1988

Direct measurement of the relative position between the end effector of robot and moving objects reduces difficulties caused by the joint encoder reading and transformation. For those purpose, the on-line sensing method using PSD sensor was developed in this paper. The sensor was calibrated on the precision table. Then, the relative position of a moving objects on the conveyor was measured while the robot was tracking the one.

• Korean Journal of Construction Engineering and Management
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• v.13 no.2
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• pp.110-119
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• 2012

The Plan and equipment of vertical lifting are very important in high-rise building construction site, and unmanned lifts usage is increasing for financial and efficient reason. However if lift stop position error occur, It can be accumulated. And the lift can not be available during an engineer fix the problem. So loss of time and cost will occur when lifts have problems. This paper reports an improved lift stop position sensing device for preventing loss of time and cost from lift stop position error. The result of tests showed that the system has a correction function of lift stop position error, and the accuracy of device which was developed in this paper was about 9.75mm better than existing equipment.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.117-124
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• 2020

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.4
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• pp.8-16
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• 1993

Auto-Pilot System uses heading angle information via the position sensor and the rudder device to control the ship direction. Most of the control logics are composed of the state estimation and control algorithms assuming that the measurement device and the actuator have no fault except the measurement noise. But such asumptions could bring the danger in real situation. For example, if the heading angle measuring device is out of order the control action based on those false position information could bring serious safety problem. In this study, the control system including improved method for processing the position information is applied to the Auto-Pilot System. To show the difference between general state estimator and F.D.F., BJDFs for the sensor and the actuator failure detection are designed and the performance are tested. And it is shown that bias error in sensor could be detected by state-augmented estimator. So the residual confined in the 2-dim in the presence of the sensor failure could be unidirectional in output space and bias sensor error is much easier to be detected.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.127-139
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• 2024

This paper discusses a gravity compensation technique designed to reduce wavefront error caused by gravity during the assembly and alignment of satellite multi-band optical sensor. For this study, the wavefront error caused by gravity was analyzed for the opto-mechanical structure of multi-band optical sensor. Wavefront error, an indicator of optical performance, was computed by using the displacements of optics calculated through structural analysis and optical sensitivity calculated through optical analysis. Since the calculated wavefront error caused by gravity exceeded the allocated budget, the gravity compensation technique was required. This compensation technique reduces wavefront error effectively by applying the compensation load to the appropriate position of the housing tube. This method successfully meets the wavefront error budget for all bands. In the future, a gravity compensation equipment applying this technique will be manufactured and used for assembly and alignment of multi-band optical sensor.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1279-1286
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• 1999

In conventional GPS/DR integration schemes, the GPS position (or pseudo-range) information is used in calibrating DR sensors. In those schemes, however, an inaccurate calibration may degrade the position accuracy when the GPS measurement is not available. This paper presents a new integration scheme where the GPS velocity information is used in calibrating DR sensors. Also proposed is a new error model of DR sensors for calibrating the bias error and the tilt error in dynamic environments. The proposed model makes it possible that the errors of both the DR sensor parameters and the velocity are calibrated using the GPS carrier-based velocity(or the pseudo-range rate) measurement while the DR position error is calibrated using the GPS position measurement. Since the DR sensors are calibrated accurately, the positioning accuracy is drastically improved when the GPS measurements are unavailable.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.78-87
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• 2008

Received signal strength indicator (RSSI) is used as one of the ranging techniques to locate dynamic sensor nodes in wireless sensor network. Before it can be used for position estimation, RSSI values must be converted to distances using path loss model. These distances among sensor nodes are combined using trilateration method to find position. This paper presents an idea which attempts to integrate both path loss model and trilateration as one algorithm without going through RSSI-distance conversion. This means it is not simply formulas combination but a whole new model was developed. Several advantages were found after integration: it is able to reduce processing load, and ensure that all values do not exceed the maximum range of 16-bit signed or unsigned numbers due to antilog operation in path loss model. The results also show that this method is able to reduce estimation error while inaccurate environmental parameters are used for RSSI-distance conversion.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.70-76
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• 2020

Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.