This paper focuses on the system for object inspection by use of a laser stripe scanner and an industrial robot. In order to ensure the precision of the scanning system, a one-stage calibration method is proposed. This scheme mainly utilizes a circular-marked board as calibration target and calibrated the scanner model and hand-to-scanner transformation simultaneously using the same reference points. Therefore the influences of the scanner calibration error on the hand-to-scanner calibration can be eliminated naturedly. Finally, some experimental results are reported and analyzed.
A robot with a laser range finder to its hand is presented for the inspection of manufactured parts. The transformation from the hand frame to the finder frame is transformed to an optimization problem by measuring a radii-known ball with unknown position information. Test results of real experiments on a motoman robot are reported and analyzed.
In order to solve the problem of early fire detection in the large space, a dynamic accumulated model is presented. The motion object is firstly obtained by using adaptive background subtraction. Three combined rules for flame detection are utilized. Dynamic accumulated model is implemented to compute the edge flicker of the motion object. Two features including circularity and area change are utilized to distinguished flame from other moving object. Experimental results indicate that the presented method has quick respond and can be used in outdoor environment.
With the development of the green manufacture, a robotic inspection system is presented to meet the requirement of remanufacturing engineering. It solves the problem of acquiring the information of the three dimensions (3D) shape feature in a timely and effective manner. As to set up this system efficiently, a calibration approach of the main part of the system, the line structured light sensor, based on a six degree of freedom (6-DOF) robot is proposed. This approach takes the advantage of the flexibility of the robot for simplifying the traditional sensor calibration approach and generates the calibration control points with concentric circle to refine the precision of locating its center. The actual experiment demonstrates that this approach is suitable for field calibration with conveniences and good accuracy.
In the production process of electronic Instrument Clusters (IC) used in automobiles, a need for automated inspection of dynamic characteristics is identified. An inspection system based on hardware-in-loop emulation and computer vision using Computer Unified Device Architecture (CUDA) is proposed. The system generates network signals that emulate a real vehicle, sends the signals to an IC to turn it into various work conditions, captures the IC’s response into a graphic processing unit for real-time computer-vision processing and records inspection results into databases. An implementation of the design and performance analysis is provided.
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