Human modeling for human–robot collaboration
暂无分享,去创建一个
J. Gregory Trafton | Laura M. Hiatt | Esube Bekele | Sangeet S. Khemlani | Cody Narber | Cody G. Narber | J. Trafton | S. Khemlani | Esube Bekele | Sangeet S. Khemlani
[1] Sangeet Khemlani,et al. The processes of inference , 2013, Argument Comput..
[2] L. Baum,et al. An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process , 1972 .
[3] Kee-Eung Kim,et al. Inverse Reinforcement Learning in Partially Observable Environments , 2009, IJCAI.
[4] Shuangquan Wang,et al. Human activity recognition with user-free accelerometers in the sensor networks , 2005, 2005 International Conference on Neural Networks and Brain.
[5] Danica Kragic,et al. Adaptive Virtual Fixtures for Machine-Assisted Teleoperation Tasks , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[6] Sangeet Khemlani,et al. Immediate inferences from quantified assertions , 2015, Quarterly journal of experimental psychology.
[7] C. Lebiere,et al. An integrated theory of list memory. , 1998 .
[8] Joshua B. Tenenbaum,et al. Bayesian Theory of Mind: Modeling Joint Belief-Desire Attribution , 2011, CogSci.
[9] Christopher W. Geib,et al. Considering State in Plan Recognition with Lexicalized Grammars , 2012, CogRob@AAAI.
[10] Ramakant Nevatia,et al. Coupled Hidden Semi Markov Models for Activity Recognition , 2007, 2007 IEEE Workshop on Motion and Video Computing (WMVC'07).
[11] Lynne E. Parker,et al. 4-dimensional local spatio-temporal features for human activity recognition , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[12] Joshua B. Tenenbaum,et al. Bayesian models of human action understanding , 2005, NIPS.
[13] Candace L. Sidner,et al. Using plan recognition in human-computer collaboration , 1999 .
[14] Redwan Alqasemi,et al. Telemanipulation Assistance Based on Motion Intention Recognition , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.
[15] Aaron F. Bobick,et al. Recognition of Visual Activities and Interactions by Stochastic Parsing , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[16] P. Johnson-Laird,et al. Children's creation of algorithms: simulations and gestures , 2016 .
[17] Cynthia Breazeal,et al. Social interactions in HRI: the robot view , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[18] Brian Scassellati,et al. Socially assistive robotics [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.
[19] Colin de la Higuera,et al. Current Trends in Grammatical Inference , 2000, SSPR/SPR.
[20] Fei-Fei Li,et al. Large-Scale Video Classification with Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[21] Christian Laugier,et al. Intentional motion on-line learning and prediction , 2008, Machine Vision and Applications.
[22] Cynthia Breazeal,et al. An Embodied Cognition Approach to Mindreading Skills for Socially Intelligent Robots , 2009, Int. J. Robotics Res..
[23] Monique Thonnat,et al. Activity Recognition from Video Sequences using Declarative Models , 2000, ECAI.
[24] Irfan A. Essa,et al. Recognizing multitasked activities from video using stochastic context-free grammar , 2002, AAAI/IAAI.
[25] Svetha Venkatesh,et al. Policy Recognition in the Abstract Hidden Markov Model , 2002, J. Artif. Intell. Res..
[26] Stefanos Nikolaidis,et al. Efficient Model Learning for Human-Robot Collaborative Tasks , 2014, ArXiv.
[27] Nando de Freitas,et al. Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks , 2000, UAI.
[28] Wolfram Burgard,et al. Learning Motion Patterns of People for Compliant Robot Motion , 2005, Int. J. Robotics Res..
[29] Maja J. Mataric,et al. Investigating Implicit Cues for User State Estimation in Human-Robot Interaction Using Physiological Measurements , 2007, RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication.
[30] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[31] P. Johnson-Laird. How We Reason , 2006 .
[32] Nate Blaylock,et al. Hierarchical Goal Recognition , 2014 .
[33] Sangeet Khemlani,et al. Automating Human Inference , 2016, Bridging@IJCAI.
[34] Michael Vande Weghe,et al. An architecture for gesture-based control of mobile robots , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).
[35] Sangeet Khemlani,et al. How people differ in syllogistic reasoning , 2016, CogSci.
[36] Eduardo Salas,et al. Planning, Shared Mental Models, and Coordinated Performance: An Empirical Link Is Established , 1999, Hum. Factors.
[37] Juan-Luis Gorricho,et al. Activity Recognition from Accelerometer Data on a Mobile Phone , 2009, IWANN.
[38] Changchun Liu,et al. Online Affect Detection and Robot Behavior Adaptation for Intervention of Children With Autism , 2008, IEEE Transactions on Robotics.
[39] Darryl W. Schneider,et al. A memory-based model of Hick’s law , 2011, Cognitive Psychology.
[40] Laura M. Hiatt,et al. A Cognitive Model of Theory of Mind , 2010 .
[41] Christian Szegedy,et al. DeepPose: Human Pose Estimation via Deep Neural Networks , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Yang Wang,et al. Human Action Recognition by Semilatent Topic Models , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[43] George Kachergis,et al. A continuous-time neural model for sequential action , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.
[44] Brian Scassellati,et al. Data-Driven Model of Nonverbal Behavior for Socially Assistive Human-Robot Interactions , 2014, ICMI.
[45] Irfan A. Essa,et al. Expectation grammars: leveraging high-level expectations for activity recognition , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[46] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[47] Sean Andrist,et al. Look Like Me: Matching Robot Personality via Gaze to Increase Motivation , 2015, CHI.
[48] J. Gregory Trafton,et al. Accommodating Human Variability in Human-Robot Teams through Theory of Mind , 2011, IJCAI.
[49] Brian Scassellati,et al. Theory of Mind for a Humanoid Robot , 2002, Auton. Robots.
[50] Chen Liang,et al. Constructing Hierarchical Concepts via Analogical Generalization , 2014, CogSci.
[51] Chao Ou-Yang,et al. Petri-net integration - An approach to support multi-agent process mining , 2011, Expert Syst. Appl..
[52] François Brémond,et al. Automatic Video Interpretation: A Novel Algorithm for Temporal Scenario Recognition , 2003, IJCAI.
[53] David W. Aha,et al. Goal Reasoning for an Autonomous Squad Member , 2015 .
[54] Prügel-BennettAdam,et al. Training HMM structure with genetic algorithm for biological sequence analysis , 2004 .
[55] Jianxin Wu. Hidden Markov model , 2018 .
[56] Rama Chellappa,et al. Machine Recognition of Human Activities: A Survey , 2008, IEEE Transactions on Circuits and Systems for Video Technology.
[57] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[58] Eric Horvitz,et al. Layered representations for human activity recognition , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.
[59] Julie A. Shah,et al. Fast target prediction of human reaching motion for cooperative human-robot manipulation tasks using time series classification , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[60] Ehud Rivlin,et al. Video Event Modeling and Recognition in Generalized Stochastic Petri Nets , 2010, IEEE Transactions on Circuits and Systems for Video Technology.
[61] Ladislau Bölöni,et al. Analyzing Team Actions with Cascading HMM , 2009, FLAIRS.
[62] Tadao Murata,et al. Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.
[63] Shlomo Zilberstein,et al. Temporal and Object Relations in Unsupervised Plan and Activity Recognition , 2015, AAAI Fall Symposia.
[64] Rama Chellappa,et al. A Constrained Probabilistic Petri Net Framework for Human Activity Detection in Video* , 2008, IEEE Transactions on Multimedia.
[65] D. Gentner. Structure‐Mapping: A Theoretical Framework for Analogy* , 1983 .
[66] C. Raymond Perrault,et al. A Plan-Based Analysis of Indirect Speech Act , 1980, CL.
[67] Svetha Venkatesh,et al. Learning Hierarchical Hidden Markov Models with General State Hierarchy , 2004, AAAI.
[68] Robert P. Goldman,et al. A Bayesian Model of Plan Recognition , 1993, Artif. Intell..
[69] Siddhartha S. Srinivasa,et al. Legibility and predictability of robot motion , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[70] B. Risfic,et al. Beyond the kalman filter - Book Review , 2004, IEEE Aerospace and Electronic Systems Magazine.
[71] Qiang Yang,et al. Boosting for transfer learning , 2007, ICML '07.
[72] Shaogang Gong,et al. Recognition of group activities using dynamic probabilistic networks , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[73] Hung Hai Bui,et al. A General Model for Online Probabilistic Plan Recognition , 2003, IJCAI.
[74] Larry S. Davis,et al. Representation and Recognition of Events in Surveillance Video Using Petri Nets , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[75] Takaki Makino,et al. Apprenticeship Learning for Model Parameters of Partially Observable Environments , 2012, ICML.
[76] Thomas Serre,et al. The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[77] Yichuan Tang,et al. Deep Learning using Linear Support Vector Machines , 2013, 1306.0239.
[78] J. Gregory Trafton,et al. Using Simulations to Model Shared Mental Models , 2007 .
[79] Zoubin Ghahramani,et al. An Introduction to Hidden Markov Models and Bayesian Networks , 2001, Int. J. Pattern Recognit. Artif. Intell..
[80] J. Gregory Trafton,et al. Building and Verifying a Predictive Model of Interruption Resumption , 2012, Proceedings of the IEEE.
[81] Yan Meng,et al. Human activity recognition in video using a hierarchical probabilistic latent model , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.
[82] Terrence Fong,et al. Collaboration, Dialogue, and Human-Robot Interaction , 2001 .
[83] Andreas Stolcke,et al. Hidden Markov Model} Induction by Bayesian Model Merging , 1992, NIPS.
[84] Bernt Schiele,et al. Discovery of activity patterns using topic models , 2008 .
[85] Marc B. Vilain,et al. Getting Serious about Parsing Plans : a Grammatical Analysis of Plan Recognition , 1990 .
[86] Robert Platt,et al. Extracting User Intent in Mixed Initiative Teleoperator Control , 2004 .
[87] Martha W. Alibali,et al. Language, gesture, action! A test of the Gesture as Simulated Action framework , 2010 .
[88] Aude Billard,et al. On Learning, Representing, and Generalizing a Task in a Humanoid Robot , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[89] Eric Horvitz,et al. A Comparison of HMMs and Dynamic Bayesian Networks for Recognizing Office Activities , 2005, User Modeling.
[90] John R. Anderson. How Can the Human Mind Occur in the Physical Universe , 2007 .
[91] Autumn B. Hostetter,et al. Visible embodiment: Gestures as simulated action , 2008, Psychonomic bulletin & review.
[92] Greg Mori,et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL., NO. 1 Human Action Recognition by Semi-Latent Topic Models , 2022 .
[93] R. Weale. Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .
[94] J. Gregory Trafton,et al. ACT-R/E , 2013, HRI 2013.
[95] Yoichi Sato,et al. Recovering the Basic Structure of Human Activities from a Video-Based Symbol String , 2007, 2007 IEEE Workshop on Motion and Video Computing (WMVC'07).
[96] Michael L. Littman,et al. Activity Recognition from Accelerometer Data , 2005, AAAI.
[97] Terrence C. Stewart,et al. Building Production Systems with Realistic Spiking Neurons , 2008 .
[98] Sarit Kraus,et al. The Evolution of Sharedplans , 1999 .
[99] Rüdiger Dillmann,et al. Markerless human motion tracking with a flexible model and appearance learning , 2009, 2009 IEEE International Conference on Robotics and Automation.
[100] J. Tenenbaum,et al. Probabilistic models of cognition: exploring representations and inductive biases , 2010, Trends in Cognitive Sciences.
[101] Siddhartha S. Srinivasa,et al. Formalizing Assistive Teleoperation , 2012, Robotics: Science and Systems.
[102] Hila Zarosim,et al. Fast and Complete Symbolic Plan Recognition: Allowing for Duration, Interleaved Execution, and Lossy Observations , 2005 .
[103] Stefan Kopp,et al. MODELING THE PRODUCTION OF COVERBAL ICONIC GESTURES BY LEARNING BAYESIAN DECISION NETWORKS , 2010, Appl. Artif. Intell..
[104] Kenneth D. Forbus,et al. MAC/FAC: A Model of Similarity-Based Retrieval , 1995, Cogn. Sci..
[105] Ana Paiva,et al. Detecting Engagement in HRI: An Exploration of Social and Task-Based Context , 2012, 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing.
[106] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[107] Hector Geffner,et al. Goal Recognition over POMDPs: Inferring the Intention of a POMDP Agent , 2011, IJCAI.
[108] Raj M. Ratwani,et al. A memory for goals model of sequence errors , 2011, Cognitive Systems Research.
[109] Roland Siegwart,et al. Robot learning from demonstration , 2004, Robotics Auton. Syst..
[110] Jay Earley,et al. An efficient context-free parsing algorithm , 1970, Commun. ACM.
[111] Michael P. Wellman,et al. Probabilistic State-Dependent Grammars for Plan Recognition , 2000, UAI.
[112] Vladimir Pavlovic,et al. A dynamic Bayesian network approach to figure tracking using learned dynamic models , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[113] D. Kahneman. Thinking, Fast and Slow , 2011 .
[114] Stuart J. Russell,et al. Dynamic bayesian networks: representation, inference and learning , 2002 .
[115] Thomas L. Griffiths,et al. Integrating Topics and Syntax , 2004, NIPS.
[116] Illah R. Nourbakhsh,et al. A survey of socially interactive robots , 2003, Robotics Auton. Syst..
[117] John R. Anderson. A Spreading Activation Theory of Memory , 1988 .
[118] Branko Ristic,et al. Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .
[119] Bruce D'Ambrosio,et al. Proceedings of the Eighth international conference on Uncertainty in artificial intelligence , 1992 .
[120] David W. Aha,et al. Increasing the Runtime Speed of Case-Based Plan Recognition , 2015, FLAIRS.
[121] Susan M. Wagner,et al. Probing the Mental Representation of Gesture: Is Handwaving Spatial?. , 2004 .
[122] Eric Horvitz,et al. Dynamic Network Models for Forecasting , 1992, UAI.
[123] Monica N. Nicolescu,et al. Understanding human intentions via Hidden Markov Models in autonomous mobile robots , 2008, 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[124] Svetha Venkatesh,et al. Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[125] K. J. Craik,et al. The nature of explanation , 1944 .
[126] Sandra Carberry,et al. Techniques for Plan Recognition , 2001, User Modeling and User-Adapted Interaction.
[127] Christian Lebiere,et al. Unsurpervised Learning in Hybrid Cognitive Architectures , 2012 .
[128] Kenneth D. Forbus,et al. Modeling perceptual similarity as analogy resolves the paradox of difference detection , 2009 .
[129] Jake K. Aggarwal,et al. Recognition of Composite Human Activities through Context-Free Grammar Based Representation , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[130] Joshua B. Tenenbaum,et al. Bayesian Modeling of Human Concept Learning , 1998, NIPS.
[131] Adam Prügel-Bennett,et al. Training HMM structure with genetic algorithm for biological sequence analysis , 2004, Bioinform..
[132] Ilkka Korhonen,et al. Detection of Daily Activities and Sports With Wearable Sensors in Controlled and Uncontrolled Conditions , 2008, IEEE Transactions on Information Technology in Biomedicine.
[133] Dana Kulic,et al. Representability of human motions by factorial hidden Markov models , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[134] Gwenn Englebienne,et al. Behavior analysis of elderly using topic models , 2014, Pervasive Mob. Comput..
[135] Odest Chadwicke Jenkins,et al. Tracking human motion and actions for interactive robots , 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[136] Jake K. Aggarwal,et al. Semantic Representation and Recognition of Continued and Recursive Human Activities , 2009, International Journal of Computer Vision.
[137] Takayuki Kanda,et al. How do people walk side-by-side? — Using a computational model of human behavior for a social robot , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[138] Andrew McCallum,et al. Information Extraction with HMM Structures Learned by Stochastic Optimization , 2000, AAAI/IAAI.
[139] Henry A. Kautz,et al. Generalized Plan Recognition , 1986, AAAI.
[140] Brian Charles Williams,et al. Concurrent Plan Recognition and Execution for Human-Robot Teams , 2014, ICAPS.
[141] Allison M. Okamura,et al. Recognition of operator motions for real-time assistance using virtual fixtures , 2003, 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. HAPTICS 2003. Proceedings..
[142] S. Eddy. Hidden Markov models. , 1996, Current opinion in structural biology.
[143] Ramakant Nevatia,et al. Hierarchical Language-based Representation of Events in Video Streams , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.