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Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study
Over the past several years there has been a considerable research inves...
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Benchmarking Off-The-Shelf Solutions to Robotic Assembly Tasks
In recent years, many learning based approaches have been studied to rea...
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Learning Dense Rewards for Contact-Rich Manipulation Tasks
Rewards play a crucial role in reinforcement learning. To arrive at the ...
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Residual Learning from Demonstration
Contacts and friction are inherent to nearly all robotic manipulation ta...
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An Interior Point Method Solving Motion Planning Problems with Narrow Passages
Algorithmic solutions for the motion planning problem have been investig...
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Supervised Learning and Reinforcement Learning of Feedback Models for Reactive Behaviors: Tactile Feedback Testbed
Robots need to be able to adapt to unexpected changes in the environment...
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A New Age of Computing and the Brain
The history of computer science and brain sciences are intertwined. In h...
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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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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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Learning Task-Specific Dynamics to Improve Whole-Body Control
In quadratic program based inverse dynamics control of underactuated, fr...
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Probabilistic Recurrent State-Space Models
State-space models (SSMs) are a highly expressive model class for learni...
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An MPC Walking Framework With External Contact Forces
In this work, we present an extension to a linear Model Predictive Contr...
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A MPC Walking Framework With External Contact Forces
In this work, we present an extension to a linear Model Predictive Contr...
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Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks
In order to robustly execute a task under environmental uncertainty, a r...
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Combining learned and analytical models for predicting action effects
One of the most basic skills a robot should possess is predicting the ef...
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A New Data Source for Inverse Dynamics Learning
Modern robotics is gravitating toward increasingly collaborative human r...
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On the Design of LQR Kernels for Efficient Controller Learning
Finding optimal feedback controllers for nonlinear dynamic systems from ...
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Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers
PID control architectures are widely used in industrial applications. De...
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Depth-Based Object Tracking Using a Robust Gaussian Filter
We consider the problem of model-based 3D-tracking of objects given dens...
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Robust Gaussian Filtering using a Pseudo Measurement
Many sensors, such as range, sonar, radar, GPS and visual devices, produ...
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Probabilistic Depth Image Registration incorporating Nonvisual Information
In this paper, we derive a probabilistic registration algorithm for obje...
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