• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.584-591
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• 2014

This paper presents a novel aided navigation method for AUV (Autonomous Underwater Vehicles). The navigation system for AUV includes several sensors such as IMU (Inertial Measurement Unit), DVL (Doppler Velocity Log) and depth sensor. In general, the $13^{th}$ order INS error model, which includes depth error, velocity error, attitude error, and the accelerometer and gyroscope biases as state variables is used with measurements from DVL and depth sensors. However, the model may degrade the estimation performance of the heading state. Therefore, the $11^{th}$ INS error model is proposed. Its validity is verified by using a degree of observability and analyzing steady state error. The performance of the proposed model is shown by the computer simulation. The results show that the performance of the reduced $11^{th}$ order error model is better than that of the conventional $13^{th}$ order error model.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1167-1172
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• 2015

This paper describes the implementation of wearable AHRS for an electromagnetic motion capture system that can trace and analyze human motion on the principal nine axes of inertial sensors. The module provides a three-dimensional (3D) attitude and heading angles combining MEMS gyroscopes, accelerometers, and magnetometers based on the extended Kalman filter, and transmits the motion data to the 3D simulation via Wi-Fi to realize the unrestrained movement in open spaces. In particular, the accelerometer in AHRS is supposed to measure only the acceleration of gravity, but when a sensor moves with an external linear acceleration, the estimated linear acceleration could compensate the accelerometer data in order to improve the precision of measuring gravity direction. In addition, when an AHRS is attached in an arbitrary position of the human body, the compensation of the axis of rotation could improve the accuracy of the motion capture system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.454-464
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• 2001

In this paper, a personal navigation system is developed using GPS and dead reckoning sensors. This personal navigation system can be used to track a person inside a building, on an urban street, and in the mountain area. GPS can provide accurate absolute position information, but it cant be used without receiving enough satellite signals. Although the inertial sensors such as gyro an accelerometer and be used without this diggiculty, the inertial sensors severely suffer from their drift errors and the magne-tometer can be easily distorted by surrounding electromagnetic field. GPS and DR sensors can be inte-grated together to overcome these problems. A new personal navigation system that can be carried wit person is developed. A pedometer. actually vertically mounted accelerometer, detects ones footstep and gyro detects heading angle. These DR sensors are integrated with GPS and the humans walking pattern provides additional navigation information for compensating the DR sensors. The field testes are performed to evaluated the proposed navigation algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1189-1195
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• 2008

We introduce a MEMS-based pedestrian dead reckoning (PDR) system. A walking navigation algorithm for pedestrians is presented and map-matching algorithm for the navigation system based on dead reckoning (DR) is proposed. The PDR is equipped on the human body and provides the position information of pedestrians. And this is able to be used in ubiquitous sensor network (USN), U-hearth monitoring system, virtual reality (VR) and etc. The PDR detects a step using a novel technique and simultaneously estimates step length. Also an azimuth of the pedestrian is calculated using a fluxgate which is the one of magnetometers. Map-matching algorithm can be formulated to integrate the positioning data with the digital road network data. Map-matching algorithm not only enables the physical location to be identified from navigation system but also improves the positioning accuracy. However most of map-matching algorithms which are developed previously are for the car navigation system (CNS). Therefore they are not appropriate to implement to pedestrian navigation system based on DR system. In this paper, we propose walking navigation system and map-matching algorithm for PDR.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1098-1102
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• 2014

Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.471-476
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• 2015

This paper presents a maximum velocity trajectory planning algorithm for differential mobile robots with wheel velocity constraint to cope with physical limits in the joint space for two-wheeled mobile robots (TMR). In previous research, the convolution operator was able to generate a central velocity that deals with the physical constraints of a mobile robot while considering the heading angles along a smooth curve in terms of time-dependent parameter. However, the velocity could not track the predefined path. An algorithm is proposed to compensate an error that occurs between the actual and driven distance by the velocity of the center of a TMR within a sampling time. The velocity commands in Cartesian space are also converted to actuator commands to drive two wheels. In the case that the actuator commands exceed the maximum velocity the trajectory is redeveloped with the compensated center velocity. The new center velocity is obtained according to the curvature of the path to provide a maximum allowable velocity meaning a time-optimal trajectory. The effectiveness of the algorithm is shown through numerical examples.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.596-603
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• 2010

This paper presents a homing guidance law of anti-ship missiles using flight path angle to achieve an impact time constraint as well as an impact angle constraint. the independent variable in the nonlinear engagement model is change d from the flight time to the heading angle of the missile. The proposed guidance law can home a missile to the target with zero miss distance as well as satisfying both of the impact angle and time constraints. The performance of the proposed guidance law is evaluated by the computer simulations.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.4
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• pp.365-370
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• 2011

This paper presents the air-to-air missile autopilot design for a $180^{\circ}$ heading reversal maneuver during boost-phase. The missile's dynamics are linearized at a set of operating points for which angle of attack controllers are designed to cover an extended flight envelope. Then, angle of attack controllers are designed for this set of points, utilizing a pole-placement approach. The controllers' gains in the proposed configuration are computed from aerodynamic coefficients and design parameters in order to satisfy designer-chosen criteria. These design parameters are the closed-loop frequency, damping ratio, and time constant; these represent the characteristics of the control system. To cope with highly nonlinear and rapidly time varying dynamics during boost-phase, the global gain-scheduled controller is obtained by interpolating the controllers' gains over variations of the angle of attack, Mach number, and center of gravity. Simulation results show that the proposed autopilot design provides satisfactory performance and possesses good [ed: or "sufficient" or "excellent"] capabilities.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.103-112
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• 2018

In this paper, a high performance underwater vehicle which can be manufactured at low cost is designed and fabricated, and its performance is verified through experiments. To improve efficiency, the Myring equation is used to design the appearance and the duct structure including the thruster is planned to increase the propulsion efficiency while reducing the drag force. Through various methods, it is secured stable waterproof performance, and also is devised to have high speed movement and turning performance. The developed underwater vehicle is equipped with a high output BLDC motor to achieve a linear speed of up to 2 m/s and can change direction rapidly with stability through four rudders. The rudders are driven by coupling a timing belt and a pulley by extending the axis of a servo motor, and are equipped at the end of the body to turn heading. In addition, for stable posture control, the roll keeps its internal center of gravity low and maintains its stability due to restoring force. By controlling the four rudders, pitch and yaw are handled by the PID controller and show stable performance. To investigate the horizontal turning performance, it is confirmed that the yaw rate controller is designed and stable yaw rate control is performed.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1044-1050
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• 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.