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NeuralSim: Augmenting Differentiable Simulators with Neural Networks
Differentiable simulators provide an avenue for closing the sim-to-real ...
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Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap
We present a differentiable simulation architecture for articulated rigi...
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Confidence-rich grid mapping
Representing the environment is a fundamental task in enabling robots to...
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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...
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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...
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Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics
A key ingredient to achieving intelligent behavior is physical understan...
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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...
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Interactive Differentiable Simulation
Intelligent agents need a physical understanding of the world to predict...
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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...
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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...
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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...
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