• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.1
• /
• pp.54-61
• /
• 2012

In this paper, the pose estimation method for the satellite GTB (Ground Test Bed) using vision/MEMS IMU (Inertial Measurement Unit) integrated system is presented. The GTB for verifying a satellite system on the ground is similar to the mobile robot having thrusters and a reaction wheel as actuators and floating on the floor by compressed air. The EKF (Extended Kalman Filter) is also used for fusion of MEMS IMU and vision system that consists of a single camera and infrared LEDs that is ceiling landmarks. The fusion filter generally utilizes the position of feature points from the image as measurement. However, this method can cause position error due to the bias of MEMS IMU when the camera image is not obtained if the bias is not properly estimated through the filter. Therefore, it is proposed that the fusion method which uses the position of feature points and the velocity of the camera determined from optical flow of feature points. It is verified by experiments that the performance of the proposed method is robust to the bias of IMU compared to the method that uses only the position of feature points.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.909-915
• /
• 2008

Recently, the interests in the development and application of unmaned robots are increasing in various fields including surveillance and reconnaissance, planet exploration, and disaster relief. Unmaned robots are usually controlled from distance using radio communications but they should be equipped with an autonomous travelling function to cope with unexpected terrains and obstacles. This means that they should be able to evaluate terrain's characteristics quantitatively using mounted sensors so as to traverse harsh natural terrains autonomously. For this purpose, this paper presents a method for extracting terrain information, that is, slope and roughness from elevation maps as a prior step of traversability analysis. Slope is extracted using the curve fitting based on the least squares method and roughness using three metrics and their weighted average. The effectiveness of the proposed method is verified on both a fractal map and the world model map of a real terrain.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.6
• /
• pp.495-500
• /
• 2013

This paper proposes a double sliding surfaces based on a sliding mode control for a tracking control of nonholonomic mobile robots in the Cartesian coordinates. In order to remove sliding surface constraints, we design the additional sliding surface for the heading angle with respect to the newly defined coordinates. Then, we define the switching law based on the posture error to combine the designed sliding surface with the previous one. By using the double sliding surfaces and the switching law, we obtain the control law for arbitrary trajectories. It is proved that the position tracking error and the heading direction error asymptotically converge to zero, respectively, with the Lyapunov stability theory. Finally, through computer simulations, we demonstrate the effectiveness of the proposed control system.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.11
• /
• pp.1036-1042
• /
• 2013

In this paper, an elderly assistance system is developed based on Xenomai, a real-time development framework cooperating with the Linux kernel. A Kinect sensor is used to recognize the behavior of the elderly and A-star search algorithm is implemented to find the shortest path to the person. The mobile robot also generates a trajectory using a digital convolution operator which is based on a Bezier curve for smooth driving. In order to follow the generated trajectory within the control period, we developed real-time tasks and compared the performance of the tracking trajectory with that of non real-time tasks. The real-time task has a better result on following the trajectory within the physical constraints which means that it is more appropriate to apply to an elderly assistant system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.2
• /
• pp.140-146
• /
• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• Proceedings of the KIPE Conference
• /
• 2003.07b
• /
• pp.663-666
• /
• 2003

This paper presents a speed controller method based on the disturbance torque observer of high performance brushless DC (BLDC) motor drives. In case of the speed control of robot arms and tracking applications with lower stiffness, we cannot design the speed controller gain to be very large from tile viewpoint of the system stability. Thus, the feedforward compensator using disturbance torque observer was proposed. This method can improve the speed characteristic without increasing the speed controller gain. The enhanced speed control performance can be achieved and the speed response against the disturbance torque can be Improved for high-performance BLDC motor drive systems in which the bandwidth of tile speed controller cannot be made large enough. Consequently, speed control for high-performance BLDC motor drives become improved. The simulation results for BLDC motor drive systems confirm the validity of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.7
• /
• pp.870-874
• /
• 2005

This paper presents capacitive tactile sensor that can detect normal and shear forces. This tactile sensor consists of index plate, sensing plate, and elastic dielectric layer. The calculated sensing character is based on the changes of space between two horizontal plate. Larger overlap areas and narrow space between top and bottom plate guarantees higher sensitivity. Tactile sense information can be calculated from the changes of phase of output signal. The symmetric arrangement of sensing plates makes the manufacturing process easier and guarantees the stability of the structure. In this paper, the sensor structure is designed, the mechanism of the Proposed sensor is theoretically explained, and the simulated result is presented.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.442-448
• /
• 2011

There are many research results about a self-localization technique of mobile robot. In this paper we present a self-localization technique based on the features of ceiling vision using a fisheye lens. The features obtained by SIFT(Scale Invariant Feature Transform) can be used to be matched between the previous image and the current image and then its optimal function is derived. The fisheye lens causes some distortion on its images naturally. So it must be calibrated by some algorithm. We here propose some methods for calibration of distorted images and design of a geometric fitness model. The proposed method is applied to laboratory and aile environment. We show its feasibility at some indoor environment.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.2
• /
• pp.101-106
• /
• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.6
• /
• pp.527-532
• /
• 2013

Depth estimation is an essential factor for robot vision, 3D scene modeling, and motion control. The depth estimation method is based on focusing values calculated in a series of images by a single camera at different distance between lens and object. In this paper, we proposed a relative depth estimation method using focus measure. The proposed method is implemented by focus value calculated for each image obtained at different lens position and then depth is finally estimated by considering relative distance of two patterns. We performed various experiments on the effective focus measures for depth estimation by using various patterns and their usefulness.