• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.105-110
• /
• 1999

This paper presents a local obstacle avoidance method for indoor mobile robots using Lane method and velocity Space Command approach. The method locates local obstacles using the information form multi-sensors, such that ultrasonic sensor array and laser scanning sensor. The method uses lane method to determine optimum collision-free heading direction of a robot. Also, it deals with the robot motion dynamics problem to reduce some vibration and guarantee fast movement as well. It yields translational and rotational velocities required to avoid the detected obstacles and to keep the robot heading direction toward goal location as close as possible. For experimental verification of the method, a mobile robot driven by two AC servo motors, equipped with 24 ultrasonic sensor array and laser scanning sensor navigates using the method through a corridor cluttered with obstacle.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.9 no.2 s.25
• /
• pp.20-25
• /
• 2006

Low frequency towed line array with high array gain and beam resolution is a long range surveillance sensor for anti-submarine warfare. The beam characteristics is however deteriorated due to the distorted line array sensor caused by low towing speed, wind, current, and towing ship maneuvering. An adaptive beamforming method is utilized in this paper to enhance the distorted line array beam performance by estimating and compensating the nonlinear array shape. A polynomial curve fitting in the least square sense is used to estimate the array shape iteratively with the distributed heading sensors data along the array. Real time array shape estimation and nonlinear array beam calculation is applied to a very long towed line array sensor system and the beam performance is evaluated and compared to the linear beamformer for the simulation and sea trial data.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.5
• /
• pp.429-435
• /
• 2011

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

• Journal of Ocean Engineering and Technology
• /
• v.11 no.3
• /
• pp.170-179
• /
• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.4
• /
• pp.255-262
• /
• 2020

In modern passive sonar systems, a towed array sensor is used to minimize the effects of own ship noise and to get a higher SNR. The thin and long towed array sensor can be guided in a non-linear form according to the maneuvering of tow-ship. If this change of the array shape is not considered, the performance of beamformer may deteriorate. In order to properly beamform the elements in the array, an accurate estimate of the array shape is required. Various techniques exist for estimating the shape of the linear array. In the case of a method using a heading sensor, the estimation performance may be degraded due to the effect of heading sensor noise. As means of removing this potential error, weighted polynomial fitting technique for estimating array shape is developed here. In order to evaluate the performance of proposed method, we conducted computer simulation. From the experiments, it was confirmed that the proposed method is more robust to noise than the conventional method.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.08a
• /
• pp.117-120
• /
• 2000

본 논문은 이동로봇이 주행 중 발생하는 heading 오차를 지자기센서를 이용하여 보정하고 주행을 정확히 제어하는 것에 관한 것이다. 일반적으로 이동로봇의 주행제어는 여러 원인에 의한 부정확성을 내포하고 있다. 예를 들어 바퀴의 부정확한 기계적 정렬, 기어의 헐거워짐, 센서 신호의 잡음과 오차, 바퀴의 미끄러짐, 평탄하지 않는 표면에 의한 제도변동 등이다. 따라서, 이동명령어 수행 시 이동로봇의 heading이 의도된 대로 유지되는지를 측정하는 오차 검출이 필요하며 이를 위한 센서 본 논문에서는 지자기센서를 이용하여 오차를 보정하였다. 실험은 무선 원격 제어되는 이동로봇에 지자기 센서를 부착하여 자계의 영향이 비교적 적은 평탄한 옥외에서 수행하였고, 실험 결과를 통해 지자기 센서를 이용한 이동로봇의 heading 오차 보정과 주행제어효과를 보여주었다.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1993.10a
• /
• pp.570-574
• /
• 1993

This paper proposes a new method of estimating the position and heading angle of a mobile robot moving on a flat surface. The proposed localization method utilizes two passive beacons and a single rotating ultrasonic sensor. The passive beacons consist of two cylinders with different diameters and reflect the ultrasonic pulses coming from the sonar sensor mounted on the mobile robot. The geometric parameter set of beacon is acquired from the sonar scan data obtained at a single mobile robot location using a new data processing algorithm. Form this parameter set, the position and heading angle of the mobile robot is determined directly. The performance and validity of the proposed method are evaluated using two beacons and a single sonar sensor attached at the pan-tilt device mounted on a mobile robot, named LCAR, in our laboratory.

• Journal of Korea Society of Industrial Information Systems
• /
• v.18 no.4
• /
• pp.37-41
• /
• 2013

A balance maintain system of Stewart platform using AHRS(Attitude and Heading Reference System) sensor is introduced. The Stewart platform is used for controlling a standing plate to keep up horizontal level at any slopes. To know current leaned degrees, AHRS sensor is used. We made feed-back system that AHRS sensor sends current status and the Stewart platform revises top plate to be equilibrium state.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.175-175
• /
• 2000

In this Paper we propose a navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with biases and measurement noise, are investigated with theoretically data from KRISO's AUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system comment)'used aboard underwater vehicle.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.2
• /
• pp.118-124
• /
• 2008

Recently fishing industry is interested in efficiency and automation to acquire the international competitive power of national fishing industry. As an automation device of fishing boat, there are electric compasses using GPS and terrestrial magnetic sensor. Electric compass can be minimum size, high effectiveness with keeping the characteristic of a magnetic compass. This can be used a heading angle sensor to construct auto-navigation system in a small size ship. This paper develop electronic compass system that has serial output signal in NMEA 0183 and demonstrates the possibility of the electronics compass in navigation system for a small sized ship.