Learning Dexterous Manipulation Policies from Experience and ...

We explore learning-based approaches for feedback control of a dexterous five-finger hand performing non-prehensile manipulation.

Abstract. We explore learning-based approaches for feedback control of a dexterous five-finger hand performing non-prehensile manipulation.

[PDF] Learning Dexterous Manipulation Policies from Experience ...

Learning Dexterous Manipulation Policies from Experience and Imitation · Vikash Kumar, Abhishek Gupta, +1 author. S. Levine · Published in arXiv.org 15 November ...

Learning Dexterous Manipulation Policies from Experience and ...

Request PDF | Learning Dexterous Manipulation Policies from Experience and Imitation | We explore learning-based approaches for feedback control of a ...

Learning Dexterous Manipulation Policies from Experience ... - dblp

Vikash Kumar, Abhishek Gupta, Emanuel Todorov, Sergey Levine: Learning Dexterous Manipulation Policies from Experience and Imitation.

[1808.00177] Learning Dexterous In-Hand Manipulation - arXiv

We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies which can perform vision-based object reorientation on a physical Shadow ...

Learning Generalizable Dexterous Manipulation from Human Grasp ...

Figure 1: Examples of our affordance demonstrations and learned policies. Left: We visualize two groups of demonstrations for each object category.

Learning dexterity | OpenAI

... Dexterous Hand, PhaseSpace motion tracking cameras, and Basler RGB cameras. For the task of block manipulation, policies trained with ...

Learning dexterous in-hand manipulation - OpenAI

Kumar V, Gupta A, Todorov E, Levine S. (2016a) Learning dexterous manipulation policies from experience and imitation. CoRR abs/1611.05095.

Learning Dexterous In-Hand Manipulation - ResearchGate

We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies ... Learning Dexterous Manipulation Policies from Experience and Imitation.

[PDF] Learning dexterous in-hand manipulation - Semantic Scholar

This work uses reinforcement learning (RL) to learn dexterous in-hand manipulation policies that can perform vision-based object reorientation on a physical ...

Learning Complex Dexterous Manipulation with Deep ... - Robotics

We demonstrate successful policies for object relocation, in-hand manipulation, tool use, and door opening, which are shown in the supplementary video. I.

Learning dexterous in-hand manipulation - Sage Journals

In this work, we demonstrate methods to train control policies that perform in-hand manipulation and deploy them on a physical robot. The resulting policy ...

Learning dexterous in-hand manipulation - ACM Digital Library

We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies that can perform vision-based object reorientation on a physical Shadow ...

Learning Dexterous In-Hand Manipulation - Matthias Plappert

In this work, we demonstrate methods to train control policies that perform in-hand manipulation and deploy them on a physical robot. The resulting policy ...

Learning Dexterous Manipulation Policies from Experience and ...

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Dexterous Manipulation with Reinforcement Learning: Efficient ...

... experience, training in 50 hours on thousands of CPU cores). ... This approach can acquire a variety of in-hand manipulation strategies from ...

Data-efficient Deep Reinforcement Learning for Dexterous ...

The paper presents and evaluates a collection of approaches to speed learning of policies for manipulation tasks. 3. Improving the data efficiency of learning ...

Generalization in Dexterous Manipulation via Geometry-Aware Multi ...

In this work, we show that policies learned by existing reinforcement learning algorithms can in fact be generalist when combined with multi-task learning and a ...

Learning Dexterous Manipulation from Suboptimal Experts

We show how suboptimal experts can be constructed effectively by composing simple waypoint tracking controllers, and we also show how learned ...