Learning Extrinsic Dexterity with Parameterized Manipulation Primitives

no code implementations • 26 Oct 2023 • Shih-Min Yang, Martin Magnusson, Johannes A. Stork, Todor Stoyanov

We solve this problem by learning a sequence of actions that utilize the environment to change the object's pose.

Friction Hierarchical Reinforcement Learning +4

Towards Task-Prioritized Policy Composition

no code implementations • 20 Sep 2022 • Finn Rietz, Erik Schaffernicht, Todor Stoyanov, Johannes A. Stork

Combining learned policies in a prioritized, ordered manner is desirable because it allows for modular design and facilitates data reuse through knowledge transfer.

reinforcement-learning Reinforcement Learning (RL) +1

Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation

no code implementations • 19 Sep 2022 • Quantao Yang, Johannes A. Stork, Todor Stoyanov

We propose to learn prior distribution over the specific skill required to accomplish each task and compose the family of skill priors to guide learning the policy for a new task by comparing the similarity between the target task and the prior ones.

reinforcement-learning Reinforcement Learning (RL)

Ensemble of Sparse Gaussian Process Experts for Implicit Surface Mapping with Streaming Data

no code implementations • 12 Feb 2020 • Johannes A. Stork, Todor Stoyanov

In this paper, we learn a compact and continuous implicit surface map of an environment from a stream of range data with known poses.