Relevant bibliographies by topics / Robot vision systems

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Robot vision systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Robot vision systems"

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Monta, Mitsuji, Naoshi Kondo, Seiichi Arima, and Kazuhiko Namba. "Robotic Vision for Bioproduction Systems." Journal of Robotics and Mechatronics 15, no. 3 (2003): 341–48. http://dx.doi.org/10.20965/jrm.2003.p0341.

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The vision system is one of the most important external sensors for an agricultural robot because the robot has to find its target among various objects in complicated background. Optical and morphological properties, therefore, should be investigated first to recognize the target object properly, when a visual sensor for agricultural robot is developed. A TV camera is widely used as a vision sensor for agricultural robot. Target image can be easily obtained by using color component images from TV camera, when the target color is different from the colors of the other objects and its backgroun
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Senoo, Taku, Yuji Yamakawa, Yoshihiro Watanabe, Hiromasa Oku, and Masatoshi Ishikawa. "High-Speed Vision and its Application Systems." Journal of Robotics and Mechatronics 26, no. 3 (2014): 287–301. http://dx.doi.org/10.20965/jrm.2014.p0287.

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<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260003/02.jpg"" width=""300"" />Batting/throwing robots </span></div> This paper introduces high-speed vision the authors developed, together with its applications. Architecture and development examples of high-speed vision are shown first in the sections that follow, then target tracking using active vision is explained. High-speed vision applied to robot control, design guidelines, and the development system for a high-speed robot are then introduced as examples. High-speed robot tasks, including
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C, Abhishek. "Development of Hexapod Robot with Computer Vision." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (2021): 1796–805. http://dx.doi.org/10.22214/ijraset.2021.37455.

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Abstract: Nowadays many robotic systems are developed with lot of innovation, seeking to get flexibility and efficiency of biological systems. Hexapod Robot is the best example for such robots, it is a six-legged robot whose walking movements try to imitate the movements of the insects, it has two sets of three legs alternatively which is used to walk, this will provide stability, flexibility and mobility to travel on irregular surfaces. With these attributes the hexapod robots can be used to explore irregular surfaces, inhospitable places, or places which are difficult for humans to access. T
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Fujita, Toyomi, Takayuki Tanaka, Satoru Takahashi, Hidenori Takauji, and Shun’ichi Kaneko. "Special Issue on Vision and Motion Control." Journal of Robotics and Mechatronics 27, no. 2 (2015): 121. http://dx.doi.org/10.20965/jrm.2015.p0121.

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Robot vision is an important robotics and mechatronics technology for realizing intelligent robot systems that work in the real world. Recent improvements in computer processing are enabling environment to be recognized and robot to be controlled based on dynamic high-speed, highly accurate image information. In industrial application, target objects are detected much more robustly and reliably through high-speed processing. In intelligent systems applications, security systems that detect human beings have recently been applied positively in computer vision. Another attractive application is
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Zeng, Rui, Yuhui Wen, Wang Zhao, and Yong-Jin Liu. "View planning in robot active vision: A survey of systems, algorithms, and applications." Computational Visual Media 6, no. 3 (2020): 225–45. http://dx.doi.org/10.1007/s41095-020-0179-3.

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Abstract Rapid development of artificial intelligence motivates researchers to expand the capabilities of intelligent and autonomous robots. In many robotic applications, robots are required to make planning decisions based on perceptual information to achieve diverse goals in an efficient and effective way. The planning problem has been investigated in active robot vision, in which a robot analyzes its environment and its own state in order to move sensors to obtain more useful information under certain constraints. View planning, which aims to find the best view sequence for a sensor, is one
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Senoo, Taku, Yuji Yamakawa, Shouren Huang, et al. "Dynamic Intelligent Systems Based on High-Speed Vision." Journal of Robotics and Mechatronics 31, no. 1 (2019): 45–56. http://dx.doi.org/10.20965/jrm.2019.p0045.

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This paper presents an overview of the high-speed vision system that the authors have been developing, and its applications. First, examples of high-speed vision are presented, and image-related technologies are described. Next, we describe the use of vision systems to track flying objects at sonic speed. Finally, we present high-speed robotic systems that use high-speed vision for robotic control. Descriptions of the tasks that employ high-speed robots center on manipulation, bipedal running, and human-robot cooperation.
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Kühnlenz, Kolja, and Martin Buss. "Multi-Focal Vision and Gaze Control Improve Navigation Performance." International Journal of Advanced Robotic Systems 9, no. 1 (2012): 25. http://dx.doi.org/10.5772/50920.

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Multi-focal vision systems comprise cameras with various fields of view and measurement accuracies. This article presents a multi-focal approach to localization and mapping of mobile robots with active vision. An implementation of the novel concept is done considering a humanoid robot navigation scenario where the robot is visually guided through a structured environment with several landmarks. Various embodiments of multi-focal vision systems are investigated and the impact on navigation performance is evaluated in comparison to a conventional mono-focal stereo set-up. The comparative studies
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Menegatti, Emanuele, and Tomas Pajdla. "Omnidirectional robot vision." Robotics and Autonomous Systems 58, no. 6 (2010): 745–46. http://dx.doi.org/10.1016/j.robot.2010.02.006.

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Chioreanu, Adrian, Stelian Brad, and Cosmin Ioanes. "Vision on Intelligent Management of Industrial Robotics Systems." Applied Mechanics and Materials 162 (March 2012): 368–77. http://dx.doi.org/10.4028/www.scientific.net/amm.162.368.

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Based on Future Internet and ITIL, cutting edge concepts and approaches related to software service systems in distributed architectures for managing information and processes in industrial robot platforms are introduced. A new approach in defining the business relation for entities that have various interests related to industrial robots, as well as tools that support the new business approach are also identified in this paper. Further the architecture of a prototype platform designed around those concepts is presented.
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Troscianko, T., B. Vincent, I. D. Gilchrist, R. Knight, and O. Holland. "A robot with active vision." Journal of Vision 6, no. 6 (2010): 456. http://dx.doi.org/10.1167/6.6.456.

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Dissertations / Theses on the topic "Robot vision systems"

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Öfjäll, Kristoffer. "Online Learning for Robot Vision." Licentiate thesis, Linköpings universitet, Datorseende, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-110892.

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In tele-operated robotics applications, the primary information channel from the robot to its human operator is a video stream. For autonomous robotic systems however, a much larger selection of sensors is employed, although the most relevant information for the operation of the robot is still available in a single video stream. The issue lies in autonomously interpreting the visual data and extracting the relevant information, something humans and animals perform strikingly well. On the other hand, humans have great diculty expressing what they are actually looking for on a low level, suitabl
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Pudney, Christopher John. "Surface modelling and surface following for robots equipped with range sensors." University of Western Australia. Dept. of Computer Science, 1994. http://theses.library.uwa.edu.au/adt-WU2003.0002.

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The construction of surface models from sensor data is an important part of perceptive robotics. When the sensor data are obtained from fixed sensors the problem of occlusion arises. To overcome occlusion, sensors may be mounted on a robot that moves the sensors over the surface. In this thesis the sensors are single–point range finders. The range finders provide a set of sensor points, that is, the surface points detected by the sensors. The sets of sensor points obtained during the robot’s motion are used to construct a surface model. The surface model is used in turn in the com
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Karr, Roger W. "The assembly of a microcomputer controlled low cost vision-robot system and the design of software." Ohio : Ohio University, 1985. http://www.ohiolink.edu/etd/view.cgi?ohiou1184010908.

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Sridaran, S. "Off-line robot vision system programming using a computer aided design system." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/54373.

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Robots with vision capability have been taught to recognize unknown objects by comparing their shape features with those of known objects, which are stored in the vision system as a knowledge base. Traditionally, this knowledge base is created by showing the robot the set of objects that it is likely to come across. This is done with the vision system to be used and must be done in an online mode. An approach to teach the robot in an off-line mode by integrating the robot vision system and an off-line graphic system, has been developed in this research. Instead of showing the objects that the
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Damweber, Michael Frank. "Model independent offset tracking with virtual feature points." Thesis, Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/17651.

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Ma, Mo. "Navigation using one camera in structured environment /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECED%202007%20MA.

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Cipolla, Roberto. "Active visual inference of surface shape." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293392.

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Jansen, van Nieuwenhuizen Rudolph Johannes. "Development of an automated robot vision component handling system." Thesis, Bloemfontein : Central University of Technology, Free State, 2013. http://hdl.handle.net/11462/213.

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Thesis (M. Tech. (Engineering: Electrical)) -- Central University of technology, Free State, 2013<br>In the industry, automation is used to optimize production, improve product quality and increase profitability. By properly implementing automation systems, the risk of injury to workers can be minimized. Robots are used in many low-level tasks to perform repetitive, undesirable or dangerous work. Robots can perform a task with higher precision and accuracy to lower errors and waste of material. Machine Vision makes use of cameras, lighting and software to do visual inspections that a
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Ukidve, Chinmay S. "Quantifying optimum fault tolerance of manipulators and robotic vision systems." Laramie, Wyo. : University of Wyoming, 2008. http://proquest.umi.com/pqdweb?did=1605147571&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.

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Hallenberg, Johan. "Robot Tool Center Point Calibration using Computer Vision." Thesis, Linköping University, Department of Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-9520.

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<p>Today, tool center point calibration is mostly done by a manual procedure. The method is very time consuming and the result may vary due to how skilled the operators are.</p><p>This thesis proposes a new automated iterative method for tool center point calibration of industrial robots, by making use of computer vision and image processing techniques. The new method has several advantages over the manual calibration method. Experimental verifications have shown that the proposed method is much faster, still delivering a comparable or even better accuracy. The setup of the proposed method is
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Books on the topic "Robot vision systems"

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1950-, Liu Z. Q., ed. Knowledge-based vision-guided robots. Physica-Verlag, 2002.

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Computer vision for robotic systems: An introduction. Prentice Hall, 1988.

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Durrant-Whyte, Hugh F. Integration, Coordination and Control of Multi-Sensor Robot Systems. Springer US, 1987.

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Dudek, Gregory. Robotic exploration as graph construction. University of Toronto, Dept. of Computer Science, 1988.

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Ruoff, Wolfgang. Optische Sensorsysteme zur On-line-Führung von Industrierobotern. Springer-Verlag, 1989.

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Mendes, Mateus. Vision-based robot navigation: Quest for intelligent approaches using a sparse distributed memory. Universal Publishers, 2012.

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Cipolla, Roberto. Active visual inference of surface shape. Springer₋Verlag, 1996.

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International Conference on Robot Vision and Sensory Controls (7th 1988 Zurich, Switzerland). Advanced sensor technology: Proceedings of the 7th International Conference on Robot Vision and Sensory Controls, 2-4 February 1988, Zürich, Switzerland. IFS Publications, 1988.

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Bräunl, Thomas. Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems. Springer Berlin Heidelberg, 2003.

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Gridin, V. N. Adaptivnye sistemy tekhnicheskogo zrenii︠a︡. "Nauka", 2009.

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Book chapters on the topic "Robot vision systems"

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McIvor, Alan, Qi Zang, and Reinhard Klette. "The Background Subtraction Problem for Video Surveillance Systems." In Robot Vision. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44690-7_22.

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Browne, Arthur, and Leonard Norton-Wayne. "Robot Systems." In Vision and Information Processing for Automation. Springer US, 1986. http://dx.doi.org/10.1007/978-1-4899-2028-7_7.

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Leclercq, Philippe, and Thomas Bräunl. "A Color Segmentation Algorithm for Real-Time Object Localization on Small Embedded Systems." In Robot Vision. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44690-7_9.

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Browne, Arthur, and Leonard Norton-Wayne. "Robot Vision Systems and Applications." In Vision and Information Processing for Automation. Springer US, 1986. http://dx.doi.org/10.1007/978-1-4899-2028-7_9.

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Tsotsos, John K. "Motion Understanding Systems." In Active Perception and Robot Vision. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77225-2_1.

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Kropatsch, Walter G. "Hierarchical Methods for Robot Vision." In Expert Systems and Robotics. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76465-3_4.

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Little, James J., Jesse Hoey, and Pantelis Elinas. "Visual Capabilities in an Interactive Autonomous Robot." In Cognitive Vision Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11414353_17.

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Balsi, Marco, and Xavier Vilasís-Cardona. "Robot Vision Using Cellular Neural Networks." In Autonomous Robotic Systems. Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-7908-1767-6_16.

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D’Hollander, Erik H. "Neural Networks and Robot Vision." In Microprocessors in Robotic and Manufacturing Systems. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3812-3_10.

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Purnell, G., and K. Khodabandehloo. "Vision for Robot Guidance in Automated Butchery." In Robotic Systems. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2526-0_71.

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Conference papers on the topic "Robot vision systems"

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Liu, Shuai, Chunlin Chen, Lihua Xie, and Yeong-Hwa Chang. "Formation control of multi-robot systems." In Vision (ICARCV 2010). IEEE, 2010. http://dx.doi.org/10.1109/icarcv.2010.5707964.

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Zhang, Xing, and Mark H. Lee. "A Developmental Robot Vision System." In 2006 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icsmc.2006.385028.

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Sitte, Joaquin, and Petra Winzer. "Methodic Design of Robot Vision Systems." In 2007 International Conference on Mechatronics and Automation. IEEE, 2007. http://dx.doi.org/10.1109/icma.2007.4303816.

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Lejun, Shao, Richard A. Volz, Lynn Conway, and Michael W. Walker. "Incorporating robot vision in teleautonomous systems." In Robotics - DL tentative, edited by William E. Stoney. SPIE, 1992. http://dx.doi.org/10.1117/12.56769.

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Barnard, S., R. Bolles, D. Marimont, and A. Pentland. "Multiple Representations for Mobile Robot Vision." In Cambridge Symposium_Intelligent Robotics Systems, edited by Nelson Marquina and William J. Wolfe. SPIE, 1987. http://dx.doi.org/10.1117/12.937793.

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Ganapathy, Velappa, and Ng Oon-Ee. "Stereo Vision Based Robot Controller." In 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2008. http://dx.doi.org/10.1109/icsmc.2008.4811558.

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Chittajallu, Siva K., and Michael A. Penna. "Incorporating Ultrasound Into Robot Vision." In 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, edited by Bruce G. Batchelor. SPIE, 1990. http://dx.doi.org/10.1117/12.969822.

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Shi, Weijie, Lei Zhang, Yang Yao, Junqiu Zuo, and Xingtian Yao. "Linear Calibration for Robot Vision." In 2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). IEEE, 2016. http://dx.doi.org/10.1109/ihmsc.2016.223.

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Reina, Giulio, Annalisa Milella, and Mario Foglia. "Vision-Based Methods for Mobile Robot Localization and Wheel Sinkage Estimation." In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2188.

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External perception based on vision plays a critical role in developing improved and robust localization algorithms for mobile robots, as well as in gaining important information about the vehicle and the traversed terrain. This paper presents two novel methods to improve mobility on rough terrains by using visual input. The first method consists of a stereovision algorithm for 6-DoF ego-motion estimation, which integrates image intensity information and 3D stereo data using an Iterative Closest Point (ICP) approach. The second method aims at estimating the wheel sinkage of a mobile robot on d
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Blake, Andrew. "Probabilistic inference in machine vision systems." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543173.

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Reports on the topic "Robot vision systems"

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Metta, Giorgio. An Attentional System for a Humanoid Robot Exploiting Space Variant Vision. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada434729.

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