Optimal tracking a moving target for integrated mobile robot-pan tilt-stereo camera

The purpose of this paper is to develop an intelligent mobile robot using image processing technology. The mobile robot is composed of a visual tracking system, a loading platform, a balance control system, a PC-based controller, four ultrasonic sensors and a power system. We develop a PC based control system for image processing and path planning. The mobile robot can track a moving target and adjust the loading platform by the balance control system simultaneously. The Image processing based on OpenCV use two different tracking methods, MTLT (Match Template Learning Tracking) and TLD (Tracking, Learning and Detection), to track moving targets. The efficiencies of both methods for tracking the moving target on the mobile robot are compared in this paper. The loading platform control system uses HOLTEK Semiconductor Company's HT66F Series 8-bit microprocessor as the processor, and receives the feedback data from the FAS-A inclinometer sensor. The controller of the loading platform uses the PID control law according to the feedback signals of the inclinometer sensor, and controls the rotation speed of the platform motor to tune the balance level. Keywords— Intelligent mobile robot, Image processing, OpenCV, MTLT, TLD, HOLTEK, FAS-A inclinometer sensor, PID control.

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A Closed Form 3D Self-Positioning algorithm for a mobile robot using vision and guide-marks

Robotica ◽

10.1017/s0263574700006421 ◽

1991 ◽

Vol 9 (3) ◽

pp. 265-274 ◽

Cited By ~ 1

Author(s):

Zeungnam Bien ◽

Ho Yeol Kwon ◽

Jeongnam Youn ◽

Il Hong Suh

Keyword(s):

Mobile Robot ◽

Closed Form ◽

Walking Robot ◽

Practical Application ◽

Detection Mechanism ◽

Camera System ◽

Stereo Camera ◽

Multiple Camera ◽

Positioning Errors ◽

Positioning Algorithm

SUMMARYIn this paper, the 3D self-positioning problem of a mobile robot is investigated under the assumption that there are given a set of guide points along with camera vision as the detection mechanism. The minimal number of guide points is discussed to determine the position and orientation of a mobile robot via a single or multiple camera system. For practical application, a closed form 3D self-positioning algorithm is proposed using a stereo camera system with triple guide points. It is further shown that a double triangular pattern is an effective guide-mark that is robust against measurement noise in feature extraction. Then, by simulation, the sensitivity of positioning errors due to image errors are analyzed. It is experimentally shown that the proposed method with triple guide points works well for a walking robot equipped with a stereo camera in laboratory environment.

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