b'Jan Peters'

An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients

Reinforcement learning methods for robotics are increasingly successful ...
07/20/2021 ∙ by João Carvalho, et al. ∙ 0 ∙ share

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Efficient and Reactive Planning for High Speed Robot Air Hockey

Highly dynamic robotic tasks require high-speed and reactive robots. The...
07/13/2021 ∙ by Puze Liu, et al. ∙ 0 ∙ share

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High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

We introduce a method based on deep metric learning to perform Bayesian ...
06/07/2021 ∙ by Antoine Grosnit, et al. ∙ 36 ∙ share

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Robust Value Iteration for Continuous Control Tasks

When transferring a control policy from simulation to a physical system,...
05/25/2021 ∙ by Michael Lutter, et al. ∙ 2 ∙ share

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Evolutionary Training and Abstraction Yields Algorithmic Generalization of Neural Computers

A key feature of intelligent behaviour is the ability to learn abstract ...
05/17/2021 ∙ by Daniel Tanneberg, et al. ∙ 0 ∙ share

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Stochastic Control through Approximate Bayesian Input Inference

Optimal control under uncertainty is a prevailing challenge in control, ...
05/17/2021 ∙ by Joe Watson, et al. ∙ 15 ∙ share

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Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning

Reactive motion generation problems are usually solved by computing acti...
05/11/2021 ∙ by Julen Urain, et al. ∙ 0 ∙ share

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Value Iteration in Continuous Actions, States and Time

Classical value iteration approaches are not applicable to environments ...
05/10/2021 ∙ by Michael Lutter, et al. ∙ 4 ∙ share

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Reinforcement Learning using Guided Observability

Due to recent breakthroughs, reinforcement learning (RL) has demonstrate...
04/22/2021 ∙ by Stephan Weigand, et al. ∙ 0 ∙ share

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Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions

Trajectory optimization and model predictive control are essential techn...
03/29/2021 ∙ by Hany Abdulsamad, et al. ∙ 0 ∙ share

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SKID RAW: Skill Discovery from Raw Trajectories

Integrating robots in complex everyday environments requires a multitude...
03/26/2021 ∙ by Daniel Tanneberg, et al. ∙ 0 ∙ share

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Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning

Substantial advancements to model-based reinforcement learning algorithm...
03/25/2021 ∙ by Andrew S. Morgan, et al. ∙ 0 ∙ share

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Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk

Discrete-time stochastic optimal control remains a challenging problem f...
03/10/2021 ∙ by Joe Watson, et al. ∙ 0 ∙ share

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Extended Task and Motion Planning of Long-horizon Robot Manipulation

Task and Motion Planning (TAMP) requires the integration of symbolic rea...
03/09/2021 ∙ by Tianyu Ren, et al. ∙ 0 ∙ share

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Learning Human-like Hand Reaching for Human-Robot Handshaking

One of the first and foremost non-verbal interactions that humans perfor...
02/28/2021 ∙ by Vignesh Prasad, et al. ∙ 0 ∙ share

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A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning

Across machine learning, the use of curricula has shown strong empirical...
02/25/2021 ∙ by Pascal Klink, et al. ∙ 21 ∙ share

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Human-Robot Handshaking: A Review

For some years now, the use of social, anthropomorphic robots in various...
02/14/2021 ∙ by Vignesh Prasad, et al. ∙ 0 ∙ share

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Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems

We present a new family of deep neural network-based dynamic systems. Th...
12/11/2020 ∙ by Julen Urain, et al. ∙ 0 ∙ share

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Perspectives on Sim2Real Transfer for Robotics: A Summary of the R:SS 2020 Workshop

This report presents the debates, posters, and discussions of the Sim2Re...
12/07/2020 ∙ by Sebastian Höfer, et al. ∙ 4 ∙ share

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Convex Optimization with an Interpolation-based Projection and its Application to Deep Learning

Convex optimizers have known many applications as differentiable layers ...
11/13/2020 ∙ by Riad Akrour, et al. ∙ 0 ∙ share

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A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning

Probabilistic regression techniques in control and robotics applications...
11/10/2020 ∙ by Hany Abdulsamad, et al. ∙ 13 ∙ share

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Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning

A limitation of model-based reinforcement learning (MBRL) is the exploit...
11/03/2020 ∙ by Michael Lutter, et al. ∙ 0 ∙ share

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Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient

Off-policy Reinforcement Learning (RL) holds the promise of better data ...
10/27/2020 ∙ by Samuele Tosatto, et al. ∙ 15 ∙ share

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Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills

Parameterized movement primitives have been extensively used for imitati...
10/26/2020 ∙ by Samuele Tosatto, et al. ∙ 1 ∙ share

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High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards

Robots that can learn in the physical world will be important to en-able...
10/26/2020 ∙ by Kai Ploeger, et al. ∙ 0 ∙ share

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ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows

We introduce ImitationFlow, a novel Deep generative model that allows le...
10/25/2020 ∙ by Julen Urain, et al. ∙ 0 ∙ share

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A Differentiable Newton Euler Algorithm for Multi-body Model Learning

In this work, we examine a spectrum of hybrid model for the domain of mu...
10/19/2020 ∙ by Michael Lutter, et al. ∙ 0 ∙ share

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Differentiable Implicit Layers

In this paper, we introduce an efficient backpropagation scheme for non-...
10/14/2020 ∙ by Andreas Look, et al. ∙ 0 ∙ share

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Active Inference or Control as Inference? A Unifying View

Active inference (AI) is a persuasive theoretical framework from computa...
10/01/2020 ∙ by Joe Watson, et al. ∙ 6 ∙ share

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Advances in Human-Robot Handshaking

The use of social, anthropomorphic robots to support humans in various i...
08/26/2020 ∙ by Vignesh Prasad, et al. ∙ 0 ∙ share

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Assisted Teleoperation in Changing Environments with a Mixture of Virtual Guides

Haptic guidance is a powerful technique to combine the strengths of huma...
08/12/2020 ∙ by Marco Ewerton, et al. ∙ 0 ∙ share

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Model-Based Quality-Diversity Search for Efficient Robot Learning

Despite recent progress in robot learning, it still remains a challenge ...
08/11/2020 ∙ by Leon Keller, et al. ∙ 0 ∙ share

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Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization

3D scene models are useful in robotics for tasks such as path planning, ...
07/04/2020 ∙ by Mikko Lauri, et al. ∙ 2 ∙ share

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Convex Regularization in Monte-Carlo Tree Search

Monte-Carlo planning and Reinforcement Learning (RL) are essential to se...
07/01/2020 ∙ by Tuan Dam, et al. ∙ 0 ∙ share

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Deterministic Inference of Neural Stochastic Differential Equations

Model noise is known to have detrimental effects on neural networks, suc...
06/16/2020 ∙ by Andreas Look, et al. ∙ 0 ∙ share

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Learning to Play Table Tennis From Scratch using Muscular Robots

Dynamic tasks like table tennis are relatively easy to learn for humans ...
06/10/2020 ∙ by Dieter Büchler, et al. ∙ 0 ∙ share

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Reinforcement Learning from a Mixture of Interpretable Experts

Reinforcement learning (RL) has demonstrated its ability to solve high d...
06/10/2020 ∙ by Riad Akrour, et al. ∙ 0 ∙ share

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Orientation Attentive Robot Grasp Synthesis

Physical neighborhoods of grasping points in common objects may offer a ...
06/09/2020 ∙ by Nikolaos Gkanatsios, et al. ∙ 0 ∙ share

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Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation

The control of nonlinear dynamical systems remains a major challenge for...
05/04/2020 ∙ by Hany Abdulsamad, et al. ∙ 8 ∙ share

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Self-Paced Deep Reinforcement Learning

Generalization and reuse of agent behaviour across a variety of learning...
04/24/2020 ∙ by Pascal Klink, et al. ∙ 0 ∙ share

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Deep Reinforcement Learning with Weighted Q-Learning

Overestimation of the maximum action-value is a well-known problem that ...
03/20/2020 ∙ by Andrea Cini, et al. ∙ 0 ∙ share

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Learning to Fly via Deep Model-Based Reinforcement Learning

Learning to control robots without requiring models has been a long-term...
03/19/2020 ∙ by Philip Becker-Ehmck, et al. ∙ 7 ∙ share

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Deep Adversarial Reinforcement Learning for Object Disentangling

Deep learning in combination with improved training techniques and high ...
03/08/2020 ∙ by Melvin Laux, et al. ∙ 0 ∙ share

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Bayesian Domain Randomization for Sim-to-Real Transfer

When learning policies for robot control, the real-world data required i...
03/05/2020 ∙ by Fabio Muratore, et al. ∙ 0 ∙ share

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Underactuated Waypoint Trajectory Optimization for Light Painting Photography

Despite their abundance in robotics and nature, underactuated systems re...
03/03/2020 ∙ by Christian Eilers, et al. ∙ 0 ∙ share

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Dimensionality Reduction of Movement Primitives in Parameter Space

Movement primitives are an important policy class for real-world robotic...
02/26/2020 ∙ by Samuele Tosatto, et al. ∙ 0 ∙ share

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Probabilistic approach to physical object disentangling

Physically disentangling entangled objects from each other is a problem ...
02/26/2020 ∙ by Joni Pajarinen, et al. ∙ 0 ∙ share

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Metric-Based Imitation Learning Between Two Dissimilar Anthropomorphic Robotic Arms

The development of autonomous robotic systems that can learn from human ...
02/25/2020 ∙ by Marcus Ebner von Eschenbach, et al. ∙ 0 ∙ share

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An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions

The Nadaraya-Watson kernel estimator is among the most popular nonparame...
01/29/2020 ∙ by Samuele Tosatto, et al. ∙ 0 ∙ share

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Evaluation of the Handshake Turing Test for anthropomorphic Robots

Handshakes are fundamental and common greeting and parting gestures amon...
01/28/2020 ∙ by Ruth Stock-Homburg, et al. ∙ 0 ∙ share

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Jan Peters

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