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Imitation learning for agile autonomous driving

https://doi.org/10.1177/0278364919880273

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/047134608x.w1046openalex-snapshot

System Identification

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Vehicle Dynamics and Control

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Real-time model learning using Incremental Sparse Spectrum Gaussian Process Regression

inferredcites →https://doi.org/10.1016/s0378-3758(00)00115-4openalex-snapshot

Improving predictive inference under covariate shift by weighting the log-likelihood function

inferredcites →https://doi.org/10.1038/nature14236openalex-snapshot

Human-level control through deep reinforcement learning

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Learning monocular reactive UAV control in cluttered natural environments

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Aggressive driving with model predictive path integral control

inferredcites →https://doi.org/10.1109/icra.2017.7989202openalex-snapshot

Information theoretic MPC for model-based reinforcement learning

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PLATO: Policy learning using adaptive trajectory optimization

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Design and use paradigms for gazebo, an open-source multi-robot simulator

inferredcites →https://doi.org/10.1109/ivs.2015.7225830openalex-snapshot

Kinematic and dynamic vehicle models for autonomous driving control design

inferredcites →https://doi.org/10.1109/ivs.2017.7995742openalex-snapshot

Baidu driving dataset and end-to-end reactive control model

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A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

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On Choosing and Bounding Probability Metrics

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Data Collection for Robust End-to-End Lateral Vehicle Control

inferredcites →https://doi.org/10.1145/1102351.1102426openalex-snapshot

High speed obstacle avoidance using monocular vision and reinforcement learning

inferredcites →https://doi.org/10.1177/0278364911430419openalex-snapshot

iSAM2: Incremental smoothing and mapping using the Bayes tree

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MPC-based approach to active steering for autonomous vehicle systems

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Modelling nonlinear vehicle dynamics with neural networks

inferredcites →https://doi.org/10.15607/rss.2018.xiv.056openalex-snapshot

Agile Autonomous Driving using End-to-End Deep Imitation Learning

inferredcites →https://doi.org/10.1561/2200000018openalex-snapshot

Online Learning and Online Convex Optimization

inferredcites →https://doi.org/10.1609/aimag.v31i1.2237openalex-snapshot

Robotics: Science and Systems (RSS)

inferredcites →https://doi.org/10.23919/acc.2017.7963716openalex-snapshot

Learning a deep neural net policy for end-to-end control of autonomous vehicles

inferredcites →https://doi.org/10.23919/acc.2017.7963824openalex-snapshot

Path-tracking for autonomous vehicles at the limit of friction

inferredcites →https://doi.org/10.48550/arxiv.1711.10127openalex-snapshot

Variational Inference for Gaussian Process Models with Linear Complexity

inferredcites →https://doi.org/10.48550/arxiv.1801.07292openalex-snapshot

Convergence of Value Aggregation for Imitation Learning

inferredcites →https://doi.org/10.48550/arxiv.1805.10413openalex-snapshot

Fast Policy Learning through Imitation and Reinforcement

inferredcites →https://doi.org/10.48550/arxiv.1810.06509openalex-snapshot

Predictor-Corrector Policy Optimization

inferredcites →https://doi.org/10.48550/arxiv.1902.07286openalex-snapshot

Online Learning with Continuous Variations: Dynamic Regret and Reductions

inferredcites →https://doi.org/10.52202/079017openalex-snapshot

Advances in Neural Information Processing Systems 37

inferredcites →https://doi.org/10.5555/1756006.1859914openalex-snapshot

Sparse Spectrum Gaussian Process Regression

inferredcites →https://doi.org/10.7551/mitpress/7503.001.0001openalex-snapshot

Advances in Neural Information Processing Systems 19

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Evolutionary vs imitation learning for neuromorphic control at the edge*

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A New Open-Source Off-Road Environment for Benchmark Generalization of Autonomous Driving

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Master Lane Change Decision-Making by Integrating Imitation Learning with Expert Rules

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iCOIL: Scenario Aware Autonomous Parking Via Integrated Constrained Optimization and Imitation Learning

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Complex Terrain Navigation via Model Error Prediction

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Towards Defensive Autonomous Driving: Collecting and Probing Driving Demonstrations of Mixed Qualities

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Risk-sensitive MPCs with Deep Distributional Inverse RL for Autonomous Driving

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High-Speed Accurate Robot Control using Learned Forward Kinodynamics and Non-linear Least Squares Optimization

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VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics

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PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving

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Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving

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inferred← citeshttps://doi.org/10.48550/arxiv.2010.12598openalex-snapshot

A Software Architecture for Autonomous Vehicles: Team LRM-B Entry in the First CARLA Autonomous Driving Challenge

inferred← citeshttps://doi.org/10.48550/arxiv.2103.03236openalex-snapshot

Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap

inferred← citeshttps://doi.org/10.48550/arxiv.2109.08473openalex-snapshot

Carl-Lead: Lidar-based End-to-End Autonomous Driving with Contrastive Deep Reinforcement Learning

inferred← citeshttps://doi.org/10.5281/zenodo.18656080openalex-snapshot

Machine Learning based Self Driving Escort Vehicle

inferred← citeshttps://doi.org/10.70675/4a9b4240zabb1z45abz8446z5a014f63e1c0openalex-snapshot

Méta-apprentissage par renforcement pour le contrôle adaptatif

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