Eric Heiden

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University of Southern California

NeuralSim: Augmenting Differentiable Simulators with Neural Networks

Differentiable simulators provide an avenue for closing the sim-to-real ...
11/09/2020 ∙ by Eric Heiden, et al. ∙ 0 ∙ share

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Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap

We present a differentiable simulation architecture for articulated rigi...
07/12/2020 ∙ by Eric Heiden, et al. ∙ 0 ∙ share

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Confidence-rich grid mapping

Representing the environment is a fundamental task in enabling robots to...
06/29/2020 ∙ by Ali-akbar Agha-mohammadi, et al. ∙ 5 ∙ share

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Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots

Planning smooth and energy-efficient motions for wheeled mobile robots i...
03/07/2020 ∙ by Eric Heiden, et al. ∙ 8 ∙ share

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LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments

Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, an...
03/03/2020 ∙ by Kamak Ebadi, et al. ∙ 0 ∙ share

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Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics

A key ingredient to achieving intelligent behavior is physical understan...
01/22/2020 ∙ by David Millard, et al. ∙ 0 ∙ share

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Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking

Light Detection and Ranging (LIDAR) sensors play an important role in th...
12/03/2019 ∙ by Eric Heiden, et al. ∙ 0 ∙ share

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Interactive Differentiable Simulation

Intelligent agents need a physical understanding of the world to predict...
05/26/2019 ∙ by Eric Heiden, et al. ∙ 0 ∙ share

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Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations

Simulation-to-real transfer is an important strategy for making reinforc...
10/04/2018 ∙ by Zhanpeng He, et al. ∙ 8 ∙ share

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Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation

Recent advancements in machine learning research have given rise to recu...
09/29/2018 ∙ by Hejia Zhang, et al. ∙ 0 ∙ share

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Scaling simulation-to-real transfer by learning composable robot skills

We present a novel solution to the problem of simulation-to-real transfe...
09/26/2018 ∙ by Ryan Julian, et al. ∙ 10 ∙ share

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Eric Heiden

Featured Co-authors

Luca Carlone

Sven Koenig

Gaurav S. Sukhatme

Ali-akbar Agha-mohammadi

Stefan Schaal

Karol Hausman

Kai O. Arras

Ragesh K. Ramachandran

Gaurav Sukhatme

Joseph J. Lim

Hejia Zhang

NeuralSim: Augmenting Differentiable Simulators with Neural Networks

Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap

Confidence-rich grid mapping

Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots

LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments

Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics

Physics-based Simulation of Continuous-Wave LIDAR for Localization, Calibration and Tracking

Interactive Differentiable Simulation

Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations

Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation

Scaling simulation-to-real transfer by learning composable robot skills