Robot Learning Lab

2018

• A. Lambert, A. Shaban, A. Raj, Z. Liu, & B. Boots

  Deep Forward and Inverse Perceptual Models for Tracking and Prediction

  Proceedings of the 2018 IEEE Conference on Robotics and Automation (ICRA-2018)

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  • arXiv

• J. Molnar, C. Cheng, L. Tiziani, B. Boots, & F. Hammond III

  Optical Sensing and Control Methods for Soft Pneumatically Actuated Robotic Manipulators

  Proceedings of the 2018 IEEE Conference on Robotics and Automation (ICRA-2018)

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• J. Dong, M. Mukadam, B. Boots, & F. Dellaert

  Sparse Gaussian Processes on Matrix Lie Groups: A Unified Framework for Optimizing Continuous-Time Trajectories

  Proceedings of the 2018 IEEE Conference on Robotics and Automation (ICRA-2018)

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• C. Cheng & B. Boots

  Convergence of Value Aggregation for Imitation Learning

  Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS-2018)

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  • PDF

• S. Srinivasan, G. J. Gordon, & B. Boots

  Learning Hidden Quantum Markov Models

  Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS-2018)

  • bibtex
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  • arXiv

2017

• C. Downey, A. Hefny, B. Li, B. Boots, & G. J. Gordon

  Predictive State Recurrent Neural Networks

  Proceedings of Advances in Neural Information Processing Systems 31 (NIPS-2017)

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  • arXiv

• A. Venkatraman, N. Rhinehart, W. Sun, L. Pinto, B. Boots, K. Kitani, & J. A. Bagnell

  Predictive State Decoders: Encoding the Future into Recurrent Networks

  Proceedings of Advances in Neural Information Processing Systems 31 (NIPS-2017)

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  • arXiv

• C. Cheng & B. Boots

  Variational Inference for Gaussian Process Models with Linear Complexity

  Proceedings of Advances in Neural Information Processing Systems 31 (NIPS-2017)

  • bibtex
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  • arXiv

• M. A. Rana, M. Mukadam, S. R. Ahmadzadeh, S. Chernova, & B. Boots

  Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning.

  Proceedings of the 1st Annual Conference on Robot Learning (CoRL-2017)

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• A. Shaban, S. Bansal, Z. Liu, I. Essa, & B. Boots

  One-Shot Learning for Semantic Segmentation

  Proceedings of the 28th British Machine Vision Conference (BMVC-2017)

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  • arXiv

• M. Mukadam, C. Cheng, X. Yan, & B. Boots

  Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference

  Proceedings of the 2017 IEEE Conference on Robotics and Automation (ICRA-2017)

  • bibtex
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  • youtube

• Y. Pan, C. Cheng, X. Yan, E. Theodorou, & B. Boots

  Deep AutoRally: End-to-End Imitation Learning for Agile Autonomous Driving

  The RSS Workshop on Learning From Demonstrations in High-Dimensional Feature Spaces

  • bibtex
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• A. S. Lambert, A. Shaban, & B. Boots

  Deep Forward and Inverse Perceptual Models for Tracking and Prediction

  The RSS Workshop on New Frontiers for Deep Learning in Robotics

  • bibtex
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  • PDF

• Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell

  Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction

  Proceedings of the 34th International Conference on Machine Learning (ICML-2017)

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  • arXiv

• E. Huang, A. Bhatia, B. Boots, & M. Mason

  Exact Bounds on the Contact-Driven Motion of a Sliding Object, With Applications to Robotic Pulling

  Proceedings of Robotics - Science and Systems XIII (RSS-2017)

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  • PDF

• G. Williams, N. Wagener, B. Goldfain, P. Drews, J. Rehg, B. Boots, & E. Theodorou.

  Information Theoretic MPC for Model-Based Reinforcement Learning

  Proceedings of the 2017 IEEE Conference on Robotics and Automation (ICRA-2017)

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  • youtube

• B. Dai, N. He, Y. Pan, B. Boots, & L. Song.

  Learning from Conditional Distributions via Dual Kernel Embeddings

  Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS-2017)

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• E. Huang, M. Mukadam, Z. Liu, & B. Boots

  Motion Planning with Graph-Based Trajectories and Gaussian Process Inference

  Proceedings of the 2017 IEEE Conference on Robotics and Automation (ICRA-2017)

  • bibtex
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  • youtube

• Y. Pan, X. Yan, E. Theodorou and B. Boots

  Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control

  Proceedings of the 2017 International Conference on Machine Learning (ICML)

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• Brian Hrolenok, Byron Boots, and Tucker Hybinette Balch

  Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems

  AAAI

  • bibtex
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• M. Mukadam, J. Dong, F. Dellaert, & B. Boots

  Simultaneous Trajectory Estimation and Planning via Probabilistic Inference

  Proceedings of Robotics - Science and Systems XIII (RSS-2017)

  • bibtex
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  • youtube
  • github

• M. A. Rana, M. Mukadam, S. R. Ahmadzadeh, S. Chernova & B. Boots

  Skill Generalization via Inference-based Planning

  RSS Workshop on Data-Driven Robotic Manipulation

  • bibtex
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• M. Mukadam, J. Dong, F. Dellaert, & B. Boots

  STEAP: Towards Online Estimation and Replanning

  RSS Workshop on POMDPs in Robotics

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• J. Dong, J. Burnham, B. Boots, G. Rains, & F. Dellaert.

  4D Crop Monitoring: Spatio-Temporal Reconstruction for Agriculture

  Proceedings of the 2017 IEEE Conference on Robotics and Automation

  • bibtex
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  • Youtube

2016

• Z. Marinho, B. Boots, A. Dragan, A. Byravan, G. J. Gordon, & S. Srinivasa.

  Functional Gradient Motion Planning in Reproducing Kernal Hilbert Spaces

  Proceedings of Robotics - Science and Systems XII

  • bibtex
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  • PDF

• M. Mukadam, X. Yan, & B. Boots

  Gaussian Process Motion Planning

  Proceedings of the 2016 IEEE Conference on Robotics and Automation (ICRA-2016)

  • bibtex
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  • youtube

• C. Cheng, and B. Boots

  Incremental Variational Sparse Gaussian Process Regression

  Advances in Neural Information Processing Systems

  • bibtex
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  • NIPS

• A. Venkatraman, W. Sun, M. Hebert, B. Boots, & J. A. Bagnell

  Inference Machines for Nonparametric Filter Learning

  Proceedings of the 25th International Joint Conference on Artificial Intelligence

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• W. Sun, A. Venkatraman, B. Boots, & J. A. Bagnell

  Learning to Filter With Predictive State Inference Machines

  • bibtex
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  • PDF

• W. Sun, R. Capobianco, G. J. Gordon, J. A. Bagnell, & B. Boots.

  Learning to Smooth with Bidirectional Predictive State Inference Machines.

  Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence

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• J. Dong, M. Mukadam, F. Dellaert, & B. Boots

  Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs

  Proceedings of Robotics - Science and Systems XII (RSS-2016)

  • bibtex
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  • youtube
  • github

• A. Venkatraman, W. Sun, M. Hebert, J. A. Bagnell, & B. Boots

  Online Instrumental Variable Regression with Applications to Online Linear System Identification

  Proceedings of the 30th Conference on Artificial Intelligence

  • bibtex
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• J. Tan, Z. Xie, B. Boots, & K. Liu.

  Simulation-Based Design of Dynamic Controllers for Humanoid Balancing

  Proceedings of the 2016 International Conference on Intelligent Robots and Systems

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• Y. Nishiyama, A. Afsharinejad, S. Naruse, B. Boots, & L. Song

  The Nonparametric Kernel Bayes Smoother

  Proceedings of the 19th International Conference on Artificial Intelligence and Statistics

  • bibtex
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2015

• X. Yan, V. Indelman, & B. Boots

  Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping

  ISRR

  • bibtex
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• X. Yan, B. Xie, L. Song, & B. Boots

  Large-Scale Gaussian Process Regression via Doubly Stochastic Gradient Descent

  ICML Workshop

  • bibtex
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• A. Shaban, M. Farajtabar, B. Xie, L. Song, & B. Boots.

  Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Methods

  Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence

  • bibtex
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• A. Byravan, M. Monfort, B. Ziebart, B. Boots, & D. Fox

  Graph-based Inverse Optimal Control for Robot Manipulation

  • bibtex
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  • PDF

• Y. Pan, X. Yan, E. Theodorou, & B. Boots

  Scalable Reinforcement Learning via Trajectory Optimization and Approximate Gaussian Process Regression

  NIPS Workshop

  • bibtex
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  • PDF

2014

• A. Venkatraman, B. Boots, M. Hebert, & J. A. Bagnell

  Data as Demonstrator with Applications to System Identification

  NIPS Workshop on Autonomously Learning Robots

  • bibtex
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  • PDF

• A. Byravan, M. Montfort, B. Ziebart, B. Boots, & D. Fox

  Layered Hybrid Inverse Optimal Control for Learning Robot Manipulation from Demonstration

  NIPS Workshop on Autonomously Learning Robots

  • bibtex
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• B. Boots, A. Byravan, & D. Fox

  Learning Predictive Models of a Depth Camera & Manipulator from Raw Execution Traces

  Proceedings of the 2014 IEEE Conference on Robotics and Automation

  • bibtex
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  • PDF

• A. Byravan, B. Boots, S. Srinivasa, & D. Fox

  Space-Time Functional Gradient Optimization for Motion Planning

  Proceedings of the 2014 IEEE Conference on Robotics and Automation

  • bibtex
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  • PDF