Current Issue : October - December Volume : 2018 Issue Number : 4 Articles : 5 Articles
Nowadays, research in autonomous underwater manipulation has demonstrated simple\napplications like picking an object from the sea floor, turning a valve or plugging and unplugging a\nconnector. These are fairly simple tasks compared with those already demonstrated by the mobile\nrobotics community, which include, among others, safe arm motion within areas populated with a\npriori unknown obstacles or the recognition and location of objects based on their 3D model to grasp\nthem. Kinect-like 3D sensors have contributed significantly to the advance of mobile manipulation\nproviding 3D sensing capabilities in real-time at low cost. Unfortunately, the underwater robotics\ncommunity is lacking a 3D sensor with similar capabilities to provide rich 3D information of the\nwork space. In this paper, we present a new underwater 3D laser scanner and demonstrate its\ncapabilities for underwater manipulation. In order to use this sensor in conjunction with manipulators,\na calibration method to find the relative position between the manipulator and the 3D laser scanner\nis presented. Then, two different advanced underwater manipulation tasks beyond the state of\nthe art are demonstrated using two different manipulation systems. First, an eight Degrees of\nFreedom (DoF) fixed-base manipulator system is used to demonstrate arm motion within a work\nspace populated with a priori unknown fixed obstacles. Next, an eight DoF free floating Underwater\nVehicle-Manipulator System (UVMS) is used to autonomously grasp an object from the bottom of a\nwater tank....
Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine\nlearning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video\nbased behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment.\nInvestigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine\nlearning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works\nin precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are\nexplained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods\nand machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally,\nadvantages of recent developed deep learning approach in toxic prediction are presented....
Spark-assisted chemical engraving (SACE) is a non-traditional machining technology\nthat is used to machine electrically non-conducting materials including glass, ceramics, and quartz.\nThe processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE\nprocess. In the present study, a machine vision method is applied to monitor and estimate the status\nof a SACE-drilled hole in quartz glass. During the machining of quartz glass, the spring-fed tool\nelectrode was pre-pressured on the quartz glass surface to feed the electrode that was in contact with\nthe machining surface of the quartz glass. In situ image acquisition and analysis of the SACE drilling\nprocesses were used to analyze the captured image of the state of the spark discharge at the tip and\nsidewall of the electrode. The results indicated an association between the accumulative size of the\nSACE-induced spark area and deepness of the hole. The results indicated that the evaluated depths\nof the SACE-machined holes were a proportional function of the accumulative spark size with a high\ndegree of correlation. The study proposes an innovative computer vision-based method to estimate\nthe deepness and status of SACE-drilled holes in real time....
The purpose of this work is to explore the design principles for a Real-Time Robotic Multi\nCamera Vision System, in a case study involving a real world competition of autonomous driving.\nDesign practices from vision and real-time research areas are applied into a Real-Time Robotic Vision\napplication, thus exemplifying good algorithm design practices, the advantages of employing the\nââ?¬Å?zero copy one passââ?¬Â methodology and associated trade-offs leading to the selection of a controller\nplatform. The vision tasks under study are: (i) recognition of a ââ?¬Å?flatââ?¬Â signal; and (ii) track following,\nrequiring 3D reconstruction. This research firstly improves the used algorithms for the mentioned\ntasks and finally selects the controller hardware. Optimization for the shown algorithms yielded\nfrom 1.5 times to 190 times improvements, always with acceptable quality for the target application,\nwith algorithm optimization being more important on lower computing power platforms. Results\nalso include a 3-cm and five-degree accuracy for lane tracking and 100% accuracy for signalling panel\nrecognition, which are better than most results found in the literature for this application. Clear\nresults comparing different PC platforms for the mentioned Robotic Vision tasks are also shown,\ndemonstrating trade-offs between accuracy and computing power, leading to the proper choice of\ncontrol platform. The presented design principles are portable to other applications, where Real-Time\nconstraints exist....
Noncontact measurement for rotational motion has advantages over the traditional method which measures rotational motion by\nmeans of installing some devices on the object, such as a rotary encoder. Cameras can be employed as remote monitoring or\ninspecting sensors to measure the angular velocity of a propeller because of their commonplace availability, simplicity, and\npotentially low cost. A defect of the measurement with cameras is to process the massive data generated by cameras. In order to\nreduce the collected data from the camera, a camera using ERS (electronic rolling shutter) is applied to measure angular\nvelocities which are higher than the speed of the camera. The effect of rolling shutter can induce geometric distortion in the\nimage, when the propeller rotates during capturing an image. In order to reveal the relationship between the angular velocity\nand the image distortion, a rotation model has been established. The proposed method was applied to measure the angular\nvelocities of the two-blade propeller and the multiblade propeller. The experimental results showed that this method could\ndetect the angular velocities which were higher than the camera speed, and the accuracy was acceptable....
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