• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.84-89
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• 2014

In this paper, an image-based visual servo control strategy for tracking a target object is applied to a camera-mounted omni-directional mobile robot. In order to get target angular velocity of each wheel from image coordinates of the target object, in general, a mathematical image Jacobian matrix is built using a camera model and a mobile robot kinematics. Unlike to the well-known mathematical image Jacobian, a simple rule-based control strategy is proposed to generate target angular velocities of the wheels in conjunction with size of the target object captured in a camera image. A camera image is divided into several regions, and a pre-defined rule corresponding to the target-located image region is applied to generate target angular velocities of wheels. The proposed algorithm is easily implementable in that no mathematical description for image Jacobian is required and a small number of rules are sufficient for target tracking. Experimental results are presented with descriptions about the overall experimental system.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.54-60
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• 2013

In this paper, a novel method called location-based delivery (LBD), which combines the short message service (SMS) and global position system (GPS), is proposed, and further, a realistic system for tracking a target's movement is developed. LBD reduces the number of short message transmissions while maintaining the location tracking accuracy within the acceptable range. The proposed approach, LBD, consists of three primary features: Short message format, location prediction, and dynamic threshold. The defined short message format is proprietary. Location prediction is performed by using the current location, moving speed, and bearing of the target to predict its next location. When the distance between the predicted location and the actual location exceeds a certain threshold, the target transmits a short message to the tracker to update its current location. The threshold is dynamically adjusted to maintain the location tracking accuracy and the number of short messages on the basis of the moving speed of the target. The experimental results show that LBD, indeed, outperforms other methods because it satisfactorily maintains the location tracking accuracy with relatively fewer messages.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.2
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• pp.30-38
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• 2003

This paper proposed PID controller for torch slider and PD controller for motor right wheel. to control the motion of two-wheeled welding mobile robot with seam tracking sensor touched on welding line. The motion control is realized in the view of keeping constant welding velocity and precise seam tracking even though the target welding line is on straight line or curved line. The position and direction of the body of the mottle robot are controlled by using signal errors between seam tracking sensor and body positioning sensor attached on the end of torch slider and body side of the mobile robot, respectively. In turning motion, the body and the torch slider are controlled by using the kinematic model related with two motions of body turning and torch sliding. The straight locomotion is controlled according to eleven control patterns obtained from displacements between two sensors of the seam tracking sensor and the body positioning sensor. The effectiveness is proven through the experimental results fur lattice type welding line. Through the experimental results, we can see that the position value of the electrode end point and the welding velocity are controlled almost constantly both in straight and turning locomotion.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.444-452
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• 2005

A new scheme for a mobile robot to track and capture a moving object using camera images is proposed. The moving object is assumed to be a point-object and is projected onto an image plane to form a geometrical constraint equation that provides the position data of the object based on the kinematics of the active camera. Uncertainties in position estimation caused by the point-object assumption are compensated for using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. In this paper, the experimental results of the tracking and capturing of a target object with the mobile robot are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.635-641
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• 2008

In this paper, we used a laser range finder (LRF) to detect both the static and dynamic obstacles for the safe navigation of a mobile robot. LRF sensor measurements containing the information of obstacle's geometry are first processed to extract the characteristic points of the obstacle in the sensor field of view. Then the dynamic states of the characteristic points are approximated using kinematic model, which are tracked by associating the measurements with Probability Data Association Filter. Finally, the collision avoidance algorithm is developed by using fuzzy decision making algorithm depending on the states of the obstacles tracked by the proposed obstacle tracking algorithm. The performance of the proposed algorithm is evaluated through experiments with the experimental mobile robot.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.1
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• pp.27-35
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• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1179-1184
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• 2007

An unmaned surveillance robot consists of rifle, laser receiver, thermal imager, color CCD camera, and laser illuminator. A human guard can be replaced with such a robot to take care dangerous surveillance tasks. Currently most of surveillance robots are mounded at a fixed post to take care of surveillance tasks. In order to watch blind areas, it is necessary to modify such a surveillance robot to become a mobile robot. In this paper, simulation based design procedure of mobile surveillance robot has been introduced. 3D CAD geometry model has been produced using Pro-Engineer. Required pen and tilt motor capacities have been analyzed using ADAMS inverse dynamics analysis. A target tracking and stabilization control algorithm of the mobile surveillance robot has been developed in order to stabilize the system from the motion of the vehicle which experiences the rough terrain. ADAMS-Matlab co-simulation has been also carried out to validate the proposed target tracking and stabilization algorithm.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.145-149
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• 2010

In this paper, we propose a kinematic approach to estimating the real-time moving object. A new scheme for a mobile robot to track and capture a moving object using images of a camera is proposed. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2796-2798
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• 2005

This Paper presents a method that a mobile robot can track persons in complex environment using particle filters. The topic of person following using mobile robot is researched in many different areas. The main problems of following a person are real time constraint, motion change of person during the tracking and occlusion with other objects. We present appearance adaptive models in a particle filter to realize robust visual tracking algorithm. Adaptive appearance model can handle occlusion with other people while target is moving.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.84-86
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• 2001

A new navigation method is developed and implemented for mobile robot. The mobile robot navigation problem has traditionally been decomposed into the path planning and path following. Unlike tracking-based system, which minimize intercept time and moved mobile robot distance for optimal rendezvous point selection. To research of random moving object uses algorithm of Adaptive Control using Auto-regressive Model. A fine motion tracking object's trajectory is predicted of Auto-regressive Algorithm. Thus, the mobile robot can travel faster than the target wi thin the robot's workspace. The can select optimal rendezvous point of various intercept time.