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Uncertainty has long been a critical area of study in robotics, particularly when robots are equipped with analytical models.
Fuzzy sets
Lotfi Asker Zadeh · 1965
Earlier work this paper cites.
Monte carlo sampling methods using markov chains and their applications
W Keith Hastings · 1970
Earlier work this paper cites.
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images
Stuart Geman and Donald Geman · 1984
Earlier work this paper cites.
Using occupancy grids for mobile robot perception and navigation
Alberto Elfes · 1989
Earlier work this paper cites.
Perspectives on the theory and practice of belief functions
Glenn Shafer · 1990
Earlier work this paper cites.
Statistical reasoning with imprecise probabilities
Peter Walley · 1991
Earlier work this paper cites.
Bayesian data analysis
Andrew Gelman, John B Carlin, Hal S Stern, and Donald B Rubin · 1995
Earlier work this paper cites.
Data fusion and sensor management: a decentralized information-theoretic approach
James Manyika and Hugh Durrant-Whyte · 1995
Earlier work this paper cites.
Exponential convergence of langevin distributions and their discrete approximations
Gareth O Roberts and Richard L Tweedie · 1996
Earlier work this paper cites.
A frontier-based approach for autonomous exploration
Brian Yamauchi · 1997
Earlier work this paper cites.
Planning and acting in partially observable stochastic domains
Leslie Pack Kaelbling, Michael L Littman, and Anthony R Cassandra · 1998
Earlier work this paper cites.
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
John Platt et al · 1999
Earlier work this paper cites.
Statistical inference
Roger L Berger and George Casella · 2001
Earlier work this paper cites.
Introduction to estimation and the kalman filter
Hugh Durrant-Whyte et al · 2001
Earlier work this paper cites.
Probabilistic robotics
Sebastian Thrun · 2002
Earlier work this paper cites.
Gaussian processes for machine learning
Matthias Seeger · 2004
Earlier work this paper cites.
Fuzzy control systems design and analysis: a linear matrix inequality approach
Kazuo Tanaka and Hua O Wang · 2004
Earlier work this paper cites.
IEEE robotics & automation magazine , 13(2):99–110, 2006
Simultaneous localization and mapping: part i · 2006
Earlier work this paper cites.
Pattern recognition and machine learning
Christopher M Bishop · 2006
Earlier work this paper cites.
Bayesian inverse reinforcement learning
Deepak Ramachandran and Eyal Amir · 2007
Earlier work this paper cites.
Robust model predictive control: A survey
Alberto Bemporad and Manfred Morari · 2007
Earlier work this paper cites.
A tutorial on conformal prediction
Glenn Shafer and Vladimir Vovk · 2008
Earlier work this paper cites.
Optimal transport: old and new , volume 338
Cédric Villani et al · 2009
Earlier work this paper cites.
Belief space planning assuming maximum likelihood observations
Robert Platt Jr, Russ Tedrake, Leslie Pack Kaelbling, and Tomas Lozano-Perez · 2010
Earlier work this paper cites.
Learning to grasp under uncertainty
Freek Stulp, Evangelos Theodorou, Jonas Buchli, and Stefan Schaal · 2011
Earlier work this paper cites.
Robust grasping under object pose uncertainty
Kaijen Hsiao, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2011
Earlier work this paper cites.
Bayesian learning via stochastic gradient langevin dynamics
Max Welling and Yee W Teh · 2011
Earlier work this paper cites.
Bayesian learning for neural networks , volume 118
Radford M Neal · 2012
Earlier work this paper cites.
Gaussian process occupancy maps
Simon T O’Callaghan and Fabio T Ramos · 2012
Earlier work this paper cites.
Bayesian optimisation for intelligent environmental monitoring
Roman Marchant and Fabio Ramos · 2012
Earlier work this paper cites.
Lightspeed computation of optimal transportation distances
M Cuturi · 2013
Earlier work this paper cites.
Legibility and predictability of robot motion
Anca D Dragan, Kenton CT Lee, and Siddhartha S Srinivasa · 2013
Earlier work this paper cites.
Reachability-based safe learning with gaussian processes
Anayo K Akametalu, Jaime F Fisac, Jeremy H Gillula, Shahab Kaynama, Melanie N Zeilinger, and Claire J Tomlin · 2014
Earlier work this paper cites.
Decision making under uncertainty: theory and application
Mykel J Kochenderfer · 2015
Earlier work this paper cites.
Kernel interpolation for scalable structured gaussian processes (kiss-gp)
Andrew Wilson and Hannes Nickisch · 2015
Earlier work this paper cites.
Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht · 2015
Earlier work this paper cites.
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations
Michael Laskey, Jonathan Lee, Caleb Chuck, David Gealy, Wesley Hsieh, Florian T Pokorny, Anca D Dragan, and Ken Goldberg · 2016
Earlier work this paper cites.
Dexterous grasping under shape uncertainty
Miao Li, Kaiyu Hang, Danica Kragic, and Aude Billard · 2016
Earlier work this paper cites.
Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
Earlier work this paper cites.
Stein variational gradient descent: A general purpose bayesian inference algorithm
Qiang Liu and Dilin Wang · 2016
Earlier work this paper cites.
Deep kernel learning
Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, and Eric P Xing · 2016
Earlier work this paper cites.
Fuzzy logic controller design for an unmanned aerial vehicle
RM Namal Bandara and Sujeetha Gaspe · 2016
Earlier work this paper cites.
Hilbert maps: Scalable continuous occupancy mapping with stochastic gradient descent
Fabio Ramos and Lionel Ott · 2016
Earlier work this paper cites.
Spatio-temporal hilbert maps for continuous occupancy representation in dynamic environments
Ransalu Senanayake, Lionel Ott, Simon O’Callaghan, and Fabio T Ramos · 2016
Earlier work this paper cites.
Unsupervised learning for physical interaction through video prediction
Chelsea Finn, Ian Goodfellow, and Sergey Levine · 2016
Earlier work this paper cites.
Social lstm: Human trajectory prediction in crowded spaces
Alexandre Alahi, Kratarth Goel, Vignesh Ramanathan, Alexandre Robicquet, Li Fei-Fei, and Silvio Savarese · 2016
Earlier work this paper cites.
Bayesian hilbert maps for dynamic continuous occupancy mapping
Ransalu Senanayake and Fabio Ramos · 2017
Earlier work this paper cites.
Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
Earlier work this paper cites.
Learning highly dynamic environments with stochastic variational inference
Ransalu Senanayake, Simon O’Callaghan, and Fabio Ramos · 2017
Earlier work this paper cites.
Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
Earlier work this paper cites.
Stan: A probabilistic programming language
Bob Carpenter, Andrew Gelman, Matthew D Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus A Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell · 2017
Earlier work this paper cites.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
Earlier work this paper cites.
Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes
Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, and Dieter Fox · 2017
Cited alongside, same era.
Sparse bayesian inference for dense semantic mapping
Lu Gan, Maani Ghaffari Jadidi, Steven A Parkison, and Ryan M Eustice · 2017
Cited alongside, same era.
Sequential bayesian optimization as a pomdp for environment monitoring with uavs
Philippe Morere, Roman Marchant, and Fabio Ramos · 2017
Cited alongside, same era.
POMDPs.jl: A framework for sequential decision making under uncertainty
Maxim Egorov, Zachary N. Sunberg, Edward Balaban, Tim A. Wheeler, Jayesh K. Gupta, and Mykel J. Kochenderfer · 2017
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Hamilton-jacobi reachability: A brief overview and recent advances
Somil Bansal, Mo Chen, Sylvia Herbert, and Claire J Tomlin · 2017
Cited alongside, same era.
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Di Feng, Ali Harakeh, Steven L Waslander, and Klaus Dietmayer · 2021
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Plgrim: Hierarchical value learning for large-scale exploration in unknown environments
Sung-Kyun Kim, Amanda Bouman, Gautam Salhotra, David D Fan, Kyohei Otsu, Joel Burdick, and Ali-akbar Agha-mohammadi · 2021
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Luíza Caetano Garaffa, Maik Basso, Andréa Aparecida Konzen, and Edison Pignaton de Freitas · 2021
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Fastrack: A modular framework for fast and guaranteed safe motion planning
Sylvia L Herbert, Mo Chen, SooJean Han, Somil Bansal, Jaime F Fisac, and Claire J Tomlin · 2017
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Porca: Modeling and planning for autonomous driving among many pedestrians
Yuanfu Luo, Panpan Cai, Aniket Bera, David Hsu, Wee Sun Lee, and Dinesh Manocha · 2018
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Foundations of the theory of probability: Second English Edition
Andreĭ Nikolaevich Kolmogorov and Albert T Bharucha-Reid · 2018
Cited alongside, same era.
Automorphing kernels for nonstationarity in mapping unstructured environments
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Predictive uncertainty estimation via prior networks
Andrey Malinin and Mark Gales · 2018
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Evidential deep learning to quantify classification uncertainty
Murat Sensoy, Lance Kaplan, and Melih Kandemir · 2018
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Deep directional statistics: Pose estimation with uncertainty quantification
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Autonomous tactile localization and mapping of objects buried in granular materials
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Uast: Uncertainty-aware siamese tracking
Dawei Zhang, Yanwei Fu, and Zhonglong Zheng · 2022
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Object detection with probabilistic guarantees: A conformal prediction approach
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Predicting future occupancy grids in dynamic environment with spatio-temporal learning
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Modeling human driving behavior through generative adversarial imitation learning
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Demo abstract: Real-time out-of-distribution detection on a mobile robot
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Fig-op: Exploring large-scale unknown environments on a fixed time budget
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Uncertainty-aware online merge planning with learned driver behavior
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Algorithms for decision making
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Disentangling epistemic and aleatoric uncertainty in reinforcement learning
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Rap: Risk-aware prediction for robust planning
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User-friendly safety monitoring system for manufacturing cobots
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Gemini: a family of highly capable multimodal models
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Robots that ask for help: Uncertainty alignment for large language model planners
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Conformal prediction beyond exchangeability
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pyribs: A bare-bones python library for quality diversity optimization
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