Robotic drilling for aerospace structures demands a high positioning accuracy of the robot, which is usually achieved through error measurement and compensation. In this paper, we report the development of a practical...Robotic drilling for aerospace structures demands a high positioning accuracy of the robot, which is usually achieved through error measurement and compensation. In this paper, we report the development of a practical monocular vision system for measurement of the relative error between the drill tool center point(TCP) and the reference hole. First, the principle of relative error measurement with the vision system is explained, followed by a detailed discussion on the hardware components, software components, and system integration. The elliptical contour extraction algorithm is presented for accurate and robust reference hole detection. System calibration is of key importance to the measurement accuracy of a vision system. A new method is proposed for the simultaneous calibration of camera internal parameters and hand-eye relationship with a dedicated calibration board. Extensive measurement experiments have been performed on a robotic drilling system. Experimental results show that the measurement accuracy of the developed vision system is higher than 0.15 mm, which meets the requirement of robotic drilling for aircraft structures.展开更多
In recent years, face recognition has often been proposed for personal identification. However, there are many difficulties with face recognition systems. For example, an imposter could Iogin the face recognition syst...In recent years, face recognition has often been proposed for personal identification. However, there are many difficulties with face recognition systems. For example, an imposter could Iogin the face recognition system by stealing the facial photograph of a person registered on the facial recognition system. The secudty of the face recognition system requires a live detection system to prevent system Iogin using photographs of a human face. This paper describes an effective, efficient face live detection method which uses physiological motion detected by estimating the eye blinks from a captured video sequence and an eye contour extraction algorithm. This technique uses the conventional active shape model with a random forest classifier trained to recognize the local appearance around each landmark. This local match provides more robustness for optimizing the fitting procedure. Tests show that this face live detection approach successfully discriminates a live human face from a photograph of the registered person＇s face to increase the face recognition system reliability.展开更多
基金supported by the National Natural Science Foundation of China(Nos.51205352 and 51221004)
文摘Robotic drilling for aerospace structures demands a high positioning accuracy of the robot, which is usually achieved through error measurement and compensation. In this paper, we report the development of a practical monocular vision system for measurement of the relative error between the drill tool center point(TCP) and the reference hole. First, the principle of relative error measurement with the vision system is explained, followed by a detailed discussion on the hardware components, software components, and system integration. The elliptical contour extraction algorithm is presented for accurate and robust reference hole detection. System calibration is of key importance to the measurement accuracy of a vision system. A new method is proposed for the simultaneous calibration of camera internal parameters and hand-eye relationship with a dedicated calibration board. Extensive measurement experiments have been performed on a robotic drilling system. Experimental results show that the measurement accuracy of the developed vision system is higher than 0.15 mm, which meets the requirement of robotic drilling for aircraft structures.
基金Supported by the National Key Basic Research and Development (973) Program of China (No.2007CB311004)
文摘In recent years, face recognition has often been proposed for personal identification. However, there are many difficulties with face recognition systems. For example, an imposter could Iogin the face recognition system by stealing the facial photograph of a person registered on the facial recognition system. The secudty of the face recognition system requires a live detection system to prevent system Iogin using photographs of a human face. This paper describes an effective, efficient face live detection method which uses physiological motion detected by estimating the eye blinks from a captured video sequence and an eye contour extraction algorithm. This technique uses the conventional active shape model with a random forest classifier trained to recognize the local appearance around each landmark. This local match provides more robustness for optimizing the fitting procedure. Tests show that this face live detection approach successfully discriminates a live human face from a photograph of the registered person＇s face to increase the face recognition system reliability.
