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Multi-feature multi-sensor method for mobile robot to track moving body

A mobile robot, multi-sensor technology, applied in instruments, image data processing, computing, etc., can solve the problem of difficult to obtain tracking effect, without considering the relationship between human and machine position, etc., to improve the description ability and reduce the possibility of tracking failure , to avoid the effect of model offset

Inactive Publication Date: 2013-08-28
BEIJING UNIV OF TECH
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  • Abstract
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AI Technical Summary

Problems solved by technology

Thombre designed an intelligent speed control algorithm by combining the motion characteristics of the robot and the motion state of the tracking target, but it is difficult to achieve a good tracking effect because it does not consider the positional relationship between the man and the machine

Method used

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  • Multi-feature multi-sensor method for mobile robot to track moving body
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  • Multi-feature multi-sensor method for mobile robot to track moving body

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Embodiment Construction

[0112] The hardware structure involved in the present invention is as figure 1 (b) shown. The stereo vision system used in the experiment is built by two FLEA2 cameras from Point Gray Company. The maximum imaging resolution of the camera is 1024×768, and the focal length is 3.5mm. The RFID system consists of a UHF card reader and two 8DBi circularly polarized antennas. The target body carries a passive RFID tag. The experimental hardware platform is a Pioneer3-DX robot.

[0113] The flow chart of the multi-feature and multi-sensor mobile robot tracking method is as follows: figure 2 shown, including the following steps:

[0114] Step 1, use the RFID system to roughly locate the human body carrying the passive tag nearby. If the tag is detected, go to the next step; otherwise, go to step four.

[0115] The specific method is as follows:

[0116] (1) Establish RFID sensor model

[0117] Establish the RFID antenna model: fix the antenna at a certain position indoors, and a...

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Abstract

The invention belongs to the crossing field of computer vision and intelligent robot, and discloses a new multi-feature multi-sensor method for a mobile robot to track a moving body. The method comprises the following steps: 1, coarsely positioning a body carrying a passive tag around a radio frequency identification (RFID) system by using the RFID system; 2, initially positioning the body in an image by using an adaptive template matching algorithm based on head and shoulder features; 3, accurately positioning the body in the image by using a multi-feature-based mean-shift algorithm; 4, predicting the moving state of the body by using a extended Kalman filter algorithm; 5, screening the acquired target position information by using a double-layer collaboration positioning mechanism; and 6, controlling the robot to move along with the body by using a robot following control algorithm. By the method, bodies with different poses can be tracked, the problem that the tracking is influenced when a target suddenly turns and is shielded is solved, and the robot can accurately, stably and continuously track the moving body.

Description

technical field [0001] The invention belongs to the intersection field of computer vision and intelligent robot, relates to a robot target tracking technology, in particular to a multi-feature multi-sensor mobile robot target tracking method. Background technique [0002] Moving human body tracking technology is one of the important issues in the field of machine vision. It is widely used in intelligent transportation, human behavior recognition, intelligent monitoring systems and other fields. Although related research has a history of decades, this problem is still a research hotspot in the fields of computer vision, pattern recognition, and especially robotics. In recent years, with the wide application and development of moving human body tracking technology in the fields of service robots and anti-terrorist robots, it has gradually become one of the most cutting-edge research directions in the field of computer vision. [0003] The mean-shift algorithm is widely used i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
Inventor 贾松敏王爽王丽佳李秀智
Owner BEIJING UNIV OF TECH
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