Academic literature on the topic 'Hidden robot'
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Journal articles on the topic "Hidden robot":
Nourian Zavareh, Mahdi, Fahimeh Nazarimehr, Karthikeyan Rajagopal, and Sajad Jafari. "Hidden Attractor in a Passive Motion Model of Compass-Gait Robot." International Journal of Bifurcation and Chaos 28, no. 14 (December 30, 2018): 1850171. http://dx.doi.org/10.1142/s0218127418501717.
Wu, Hongmin, Yisheng Guan, and Juan Rojas. "Analysis of multimodal Bayesian nonparametric autoregressive hidden Markov models for process monitoring in robotic contact tasks." International Journal of Advanced Robotic Systems 16, no. 2 (March 1, 2019): 172988141983484. http://dx.doi.org/10.1177/1729881419834840.
Chen, Tianyan, Jinsong Lin, Deyu Wu, and Haibin Wu. "Research of Calibration Method for Industrial Robot Based on Error Model of Position." Applied Sciences 11, no. 3 (January 31, 2021): 1287. http://dx.doi.org/10.3390/app11031287.
Kheddar, A., C. Tzafestas, and P. Coiffet. "Hidden robot concept — High level abstraction teleoperation." Computer Standards & Interfaces 20, no. 6-7 (March 1999): 433. http://dx.doi.org/10.1016/s0920-5489(99)90875-9.
Kheddar, A. "Teleoperation based on the hidden robot concept." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 31, no. 1 (2001): 1–13. http://dx.doi.org/10.1109/3468.903862.
Fox, Maria, Malik Ghallab, Guillaume Infantes, and Derek Long. "Robot introspection through learned hidden Markov models." Artificial Intelligence 170, no. 2 (February 2006): 59–113. http://dx.doi.org/10.1016/j.artint.2005.05.007.
Savage, Jesus, Oscar Fuentes, Luis Contreras, and Marco Negrete. "Map representation using hidden markov models for mobile robot localization." MATEC Web of Conferences 161 (2018): 03011. http://dx.doi.org/10.1051/matecconf/201816103011.
Durdu, Akif, Aydan M. Erkmen, and Alper Yilmaz. "Reshaping human intention in Human-Robot Interactions by robot moves." Interaction Studies 20, no. 3 (November 18, 2019): 530–60. http://dx.doi.org/10.1075/is.18068.dur.
Murao, Hajime, and Shinzo Kitamura. "Building up Embodiment in Learning Agents Using A Gaussian Radial Basis Function Neural Network." Journal of Robotics and Mechatronics 12, no. 6 (December 20, 2000): 656–63. http://dx.doi.org/10.20965/jrm.2000.p0656.
ALNAJJAR, FADY, and KAZUYUKI MURASE. "SELF-ORGANIZATION OF SPIKING NEURAL NETWORK THAT GENERATES AUTONOMOUS BEHAVIOR IN A REAL MOBILE ROBOT." International Journal of Neural Systems 16, no. 04 (August 2006): 229–39. http://dx.doi.org/10.1142/s0129065706000640.
Dissertations / Theses on the topic "Hidden robot":
Reynaga, Barba Valeria. "Detecting Changes During the Manipulation of an Object Jointly Held by Humans and RobotsDetektera skillnader under manipulationen av ett objekt som gemensamt hålls av människor och robotar." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-174027.
Seyhan, Seyit Sabri. "Simple And Complex Behavior Learning Using Behavior Hidden Markov Model And Cobart." Phd thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615508/index.pdf.
s base abilities in the categorization phase. In the modeling phase, Behavior-HMM, a modified version of hidden Markov model, is used to model the relationships among the motion primitives in a finite state stochastic network. In addition, a motion generator which is an artificial neural network is trained for each motion primitive to learn essential robot motor commands. In the generation phase, desired task is presented as a target observation and the model generates corresponding motion primitive sequence. Then, these motion primitives are executed successively by the motion generators which are specifically trained for the corresponding motion primitives. The models are not proposed for one specific behavior, but are intended to be bases for all behaviors. CBLM enhances learning capabilities by integrating previously learned behaviors hierarchically. Hence, new behaviors can take advantage of already discovered behaviors. The proposed models are tested on a robot simulator and the experiments showed that simple and complex-behavior learning models can generate requested behaviors effectively.
Zhu, Minglei. "Control-based design of Robots." Thesis, Ecole centrale de Nantes, 2020. http://www.theses.fr/2020ECDN0043.
It is well -known that parallel robots have a lot of applications in industry for their high stiffness , high payload , can reach higher acceleration and speed . However , because of their complex structure , their control may be troublesome. When high accuracy is needed, the detailed robot model is necessary . However , even detailed models still suffer from the problem of inaccuracy in reality because of robot assembly and manufacturing errors . Sensor - based control approaches have been proven to be more efficient than model-based controllers in terms of accuracy since they overcome the complex robot models and inconsistency errors. Nevertheless, when applying the visual servoing, there are always some problems in the control process , such as the controller singularities . Thus , this thesis proposes proposes a control based design metodology which takes into account the accuracy performance of the controller in the design process to get the geometric parameters of the robot. This thesis applied the control-based design methodology to the optimal design of three types of parallel robots: Five-bar mechanisms , DELTA robots , Gough -Stewart platforms . Three types of controllers are selected in the design process : leg -direction -based visual servoing, line-baesd visual servoing and image moment visual servoing . Design optimization problems are formulated to find the geometric parameters of the robot . Co-simulations are performed to check the accuracy performance of the robots obtained from the optimization. Experiments are performed with two DELTA robot prototypes in order to validate the controller accuracy
Khokar, Karan Hariharan. "Human Intention Recognition Based Assisted Telerobotic Grasping of Objects in an Unstructured Environment." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4909.
Wåhlin, Peter. "Enhanching the Human-Team Awareness of a Robot." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16371.
Användningen av autonoma robotar i vårt samhälle ökar varje dag och en robot ses inte längre som ett verktyg utan som en gruppmedlem. Robotarna arbetar nu sida vid sida med oss och ger oss stöd under farliga arbeten där människor annars är utsatta för risker. Denna utveckling har i sin tur ökat behovet av robotar med mer människo-medvetenhet. Därför är målet med detta examensarbete att bidra till en stärkt människo-medvetenhet hos robotar. Specifikt undersöker vi möjligheterna att utrusta autonoma robotar med förmågan att bedöma och upptäcka olika beteenden hos mänskliga lag. Denna förmåga skulle till exempel kunna användas i robotens resonemang och planering för att ta beslut och i sin tur förbättra samarbetet mellan människa och robot. Vi föreslår att förbättra befintliga aktivitetsidentifierare genom att tillföra förmågan att tolka immateriella beteenden hos människan, såsom stress, motivation och fokus. Att kunna urskilja lagaktiviteter inom ett mänskligt lag är grundläggande för en robot som ska vara till stöd för laget. Dolda markovmodeller har tidigare visat sig vara mycket effektiva för just aktivitetsidentifiering och har därför använts i detta arbete. För att en robot ska kunna ha möjlighet att ge ett effektivt stöd till ett mänskligtlag måste den inte bara ta hänsyn till rumsliga parametrar hos lagmedlemmarna utan även de psykologiska. För att tyda psykologiska parametrar hos människor förespråkar denna masteravhandling utnyttjandet av mänskliga kroppssignaler. Signaler så som hjärtfrekvens och hudkonduktans. Kombinerat med kroppenssignalerar påvisar vi möjligheten att använda systemdynamiksmodeller för att tolka immateriella beteenden, vilket i sin tur kan stärka människo-medvetenheten hos en robot.
The thesis work was conducted in Stockholm, Kista at the department of Informatics and Aero System at Swedish Defence Research Agency.
Dib, Abdallah. "Vers un système de capture du mouvement humain en 3D pour un robot mobile évoluant dans un environnement encombré." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0045/document.
In this thesis we are interested in designing a mobile robot able to analyze the behavior and movement of a a person in indoor and cluttered environment. Our goal is to equip the robot by visual perception capabilities of the human posture to better analyze situations that require understanding of person with which the robot interacts, or detect risk situations such as falls or analyze motor skills of the person. Motion capture in a dynamic and crowded environment raises multiple challenges such as learning the background of the environment and extracting the silhouette that can be partially observable when the person is in hidden places. These difficulties make motion capture difficult. Most of existing methods assume that the scene is static and the person is always fully visible by the camera. These approaches are not able to work in such realistic conditions. In this thesis, We propose a new motion capture system capable of tracking a person in realistic world conditions. Our approach uses a 3D occupancy grid with a hidden Markov model to continuously learn the changing background of the scene and to extract silhouette of the person, then a hierarchical particle filtering algorithm is used to reconstruct the posture. We propose a novel occlusion management algorithm able to identify and discards hidden body parts of the person from process of the pose estimation. We also proposed a new database containing RGBD images with ground truth data in order to establish a new benchmark for the assessment of motion capture systems in a real environment with occlusions. The ground truth is obtained from a motion capture system based on high-precision marker with eight infrared cameras. All data is available online. The second contribution of this thesis is the development of a new visual odometry method to localize an RGB-D camera mounted on a robot moving in a dynamic environment. The major difficulty of the localization in a dynamic environment, is that mobile objects in the scene induce additional movement that generates outliers pixels. These pixels should be excluded from the camera motion estimation process in order to produce accurate and precise localization. We thus propose an extension of the dense localization method based on the optical flow method to remove outliers pixels using the RANSAC algorithm
Alves, Roberson Junior Fernandes. "RASTREAMENTO DE AGROBOTS EM ESTUFAS AGRÍCOLAS USANDO MODELOS OCULTOS DE MARKOV: Comparação do desempenho e da correção dos algoritmos de Viterbi e Viterbi com janela de observações deslizante." UNIVERSIDADE ESTADUAL DE PONTA GROSSA, 2015. http://tede2.uepg.br/jspui/handle/prefix/132.
Developing mobile and autonomous agrobots for greenhouses requires the use of procedures which allow robot autolocalization and tracking. The tracking problem can be modeled as finding the most likely sequence of states in a hidden Markov model„ whose states indicate the positions of an occupancy grid. This sequence can be estimated with Viterbi’s algorithm. However, the processing time and consumed memory, of this algorithm, grows with the dimensions of the grid and tracking duration, and, this can constraint its use for tracking agrobots. Considering it, this work presents a tracking procedure which uses two approximated implementations of Viterbi’s algorithm called Viterbi-JD(Viterbi’s algorithm with a sliding window) and Viterbi-JD-MTE(Viterbi’s algorithm with a sliding window over an hidden Markov model with sparse transition matrix). The experimental results show that the time and memory performance of tracking with this two approximated implementations are significantly higher than the Viterbi’s based tracking. The reported tracking hypothesis is suboptimal, when compared to the hypothesis generated by Viterbi, but the error does not grows substantially. Th experimentos was performed using RSSI(Received Signal Strength Indicator) simulated data.
O desenvolvimento de agrobots móveis e autônomos para operar em estufas agrícolas depende da implementação de procedimentos que permitam o rastreamento do robô no ambiente. O problema do rastreamento pode ser modelado como a determinação da sequência de estados mais prováveis de um modelo oculto de Markov cujos estados indicam posições de uma grade de ocupação. Esta sequência pode ser estimada pelo algoritmo de Viterbi. No entanto, o tempo de processamento e a memória consumida, por esse algoritmo, crescem com as dimensões da grade e com a duração do rastreamento, e isto pode limitar seu uso no rastreamento de agrobots em estufas. Considerando o exposto, este trabalho apresenta um procedimento de rastreamento que utiliza mplementações aproximadas do algoritmo de Viterbi denominadas de Viterbi-JD(Viterbi com janela deslizante) e Viterbi- JD-MTE(Viterbi com janela deslizante sobre um modelo oculto de Markov com matriz de transição esparsa). Os experimentos mostram que o desempenho de tempo e memória do rastreamento baseado nessas implementações aproximadas é significativamente melhor que aquele do algoritmo original. A hipótese de rastreamento gerada é sub ótima em relação àquela calculada pelo algoritmo original, contudo, não há um aumento substancial do erro. Os experimentos foram realizados utilizando dados simulados de RSSI (Received Signal Strength Indicator).
Blume-Werry, Gesche. "The hidden life of plants : fine root dynamics in northern ecosystems." Doctoral thesis, Umeå universitet, Institutionen för ekologi, miljö och geovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-124757.
Ngan, Choi-chik, and 顔才績. "A hidden Markov model approach to force-based contact recognition for intelligent robotic assembly." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31243496.
Wang, Ming [Verfasser], Ian T. [Gutachter] Baldwin, Ralf [Gutachter] Oelmüller, and Le [Gutachter] Kang. "A hidden mystery : root adaptive responses to environmental factors in Nicotiana attenuata / Ming Wang ; Gutachter: Ian T. Baldwin, Ralf Oelmüller, Le Kang." Jena : Friedrich-Schiller-Universität Jena, 2018. http://d-nb.info/1205885153/34.
Books on the topic "Hidden robot":
Meinig, George. Root canal cover-up exposed!: Many illness result : dentist to the stars discovers hidden truth-- tells what to do. Ojai, Calif: Bion Pub., 1993.
Whitney, R. D. The hidden enemy: Root rot technology transfer ; for practical use in the field : a forester's guide to identification and reduction of major root rots in Ontario. [Ottawa, Ont.]: Minister of Supply and Services Canada, 1988.
Schwartz, Steven A. The Big Book of Nintendo Games. Greensboro, USA: Compute Books, 1991.
Fung, Jason, and Benjamin Bikman. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease―and How to Fight It. BenBella Books, 2020.
Bikman, Benjamin. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease--and How to Fight It. Blackstone Publishing, 2020.
Bikman, Benjamin. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease--and How to Fight It. Blackstone Publishing, 2020.
Bikman, Benjamin. Why We Get Sick: The Hidden Epidemic at the Root of Most Chronic Disease and How to Fight It. BenBella Books, 2021.
Moritz, Andreas. Cancer Is Not a Disease!: It's a Healing Mechanism; Discover Cancer's Hidden Purpose, Heal Its Root Causes, and Be Healthier Than Ever. Blackstone Audio, Inc., 2012.
Heiner, Prof, Bielefeldt, Ghanea Nazila, Dr, and Wiener Michael, Dr. Part 2 Discrimination, 2.1 Discrimination on the Basis of Religion or Belief/Interreligious Discrimination/Tolerance. Oxford University Press, 2016. http://dx.doi.org/10.1093/law/9780198703983.003.0017.
Liang, Xiaodon. Curbing Illicit Financial Flows. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805373.003.0013.
Book chapters on the topic "Hidden robot":
Coste, Michel, Philippe Wenger, and Damien Chablat. "Hidden Cusps." In Advances in Robot Kinematics 2016, 129–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56802-7_14.
García-Álvarez, Francisco Manuel, and Matilde Santos. "Educational-Oriented Mobile Robot: Hidden Lessons." In Advances in Intelligent Systems and Computing, 61–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57799-5_7.
Noda, Itsuki. "Hidden Markov Modeling of Team-Play Synchronization." In RoboCup 2003: Robot Soccer World Cup VII, 102–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25940-4_9.
Briot, Sébastien, Victor Rosenzveig, and Philippe Martinet. "The Hidden Robot Concept: A Tool for Control Analysis and Robot Control-Based Design." In Advances in Robot Kinematics, 31–39. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06698-1_4.
Boudnaya, Jaouad, Amine Haytoumi, Omar Eddayer, and Abdelhak Mkhida. "Prediction of Robot Localization States Using Hidden Markov Models." In Advances in Intelligent Systems and Computing, 253–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51186-9_18.
Noda, Itsuki. "Hidden Markov Modeling of Multi-agent Systems and Its Learning Method." In RoboCup 2002: Robot Soccer World Cup VI, 94–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45135-8_8.
Tanwani, Ajay Kumar, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, and Sylvain Calinon. "Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models." In Springer Proceedings in Advanced Robotics, 196–211. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44051-0_12.
Lochan, Kshetrimayum, Jay Prakash Singh, Binoy Krishna Roy, and Bidyadhar Subudhi. "Hidden Chaotic Path Planning and Control of a Two-Link Flexible Robot Manipulator." In Nonlinear Dynamical Systems with Self-Excited and Hidden Attractors, 433–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71243-7_19.
Pinheiro, Paulo Gurgel, Josue J. G. Ramos, Vander L. Donizete, Pedro Picanço, and Gustavo H. De Oliveira. "Workplace Emotion Monitoring—An Emotion-Oriented System Hidden Behind a Receptionist Robot." In Mechatronics and Robotics Engineering for Advanced and Intelligent Manufacturing, 407–20. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33581-0_32.
Balali, Sogol, Ross T. Sowell, William D. Smart, and Cindy M. Grimm. "Privacy Concerns in Robot Teleoperation: Does Personality Influence What Should Be Hidden?" In Social Robotics, 719–29. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35888-4_67.
Conference papers on the topic "Hidden robot":
Ferguson, D., A. Stentz, and S. Thrun. "PAO for planning with hidden state." In IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004. IEEE, 2004. http://dx.doi.org/10.1109/robot.2004.1307491.
Shepherd, David C., Nicholas A. Kraft, and Patrick Francis. "Visualizing the "Hidden" Variables in Robot Programs." In 2019 IEEE/ACM 2nd International Workshop on Robotics Software Engineering (RoSE). IEEE, 2019. http://dx.doi.org/10.1109/rose.2019.00007.
Jingjin Yu and Steven M. LaValle. "Tracking hidden agents through shadow information spaces." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543562.
Lu, Wei-zhou, and Shun-zheng Yu. "Web Robot Detection Based on Hidden Markov Model." In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.285024.
Thorniley, James, and Phil Husbands. "Hidden information transfer in an autonomous swinging robot." In European Conference on Artificial Life 2013. MIT Press, 2013. http://dx.doi.org/10.7551/978-0-262-31709-2-ch074.
Dongheui Lee, Dana Kulic, and Yoshihiko Nakamura. "Missing motion data recovery using factorial hidden Markov models." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543449.
Kulic, Dana, and Elizabeth Croft. "Estimating Robot Induced Affective State using Hidden Markov Models." In ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 2006. http://dx.doi.org/10.1109/roman.2006.314427.
Miller, Nicholas, Mohan A. Thomas, Justin A. Eichel, and Akshaya Mishra. "A Hidden Markov Model for Vehicle Detection and Counting." In 2015 12th Conference on Computer and Robot Vision (CRV). IEEE, 2015. http://dx.doi.org/10.1109/crv.2015.42.
Wu, Hongmin, Hongbin Lin, Yisheng Guan, Kensuke Harada, and Juan Rojas. "Robot introspection with Bayesian nonparametric vector autoregressive hidden Markov models." In 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). IEEE, 2017. http://dx.doi.org/10.1109/humanoids.2017.8246976.
Sarmiento, Carlos, Jesus Savage, Alfredo Juarez, Luis Contreras, Abel Pacheco, and Mauricio Matamoros. "Feature detection using Hidden Markov Models for 3D-visual recognition." In 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2019. http://dx.doi.org/10.1109/icarsc.2019.8733651.