Demonstration-Guided Deep Reinforcement Learning of Control Policies for Dexterous Human-Robot Interaction

2019-06-27 · Sammy Christen, Stefan Stevsic, Otmar Hilliges

In this paper, we propose a method for training control policies for human-robot interactions such as handshakes or hand claps via Deep Reinforcement Learning. The policy controls a humanoid Shadow Dexterous Hand, attached to a robot arm. We propose a parameterizable multi-objective reward function that allows learning of a variety of interactions without changing the reward structure. The parameters of the reward function are estimated directly from motion capture data of human-human interactions in order to produce policies that are perceived as being natural and human-like by observers. We evaluate our method on three significantly different hand interactions: handshake, hand clap and finger touch. We provide detailed analysis of the proposed reward function and the resulting policies and conduct a large-scale user study, indicating that our policy produces natural looking motions.

📄 PDF Abstract BibTeX arXiv:1906.11695

Code (0)

등록된 구현이 없습니다.

Tasks

Deep Reinforcement Learningreinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration

2026-06-22 · Xinghao Zhu, Zixi Liu, Shalin Jain, Chenran Li 외 arxiv

Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains challenging. We present Contact Wrench Guidance from Human Demonstration…

Reinforcement Learning Robot Manipulation

Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation

2022-03-24 · Sridhar Pandian Arunachalam, Sneha Silwal, Ben Evans, Lerrel Pinto

Optimizing behaviors for dexterous manipulation has been a longstanding challenge in robotics, with a variety of methods from model-based control to model-free reinforcement learning having been previously explored in li…

Imitation Learning

Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration

2016-03-21 · Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel

Dexterous multi-fingered hands can accomplish fine manipulation behaviors that are infeasible with simple robotic grippers. However, sophisticated multi-fingered hands are often expensive and fragile. Low-cost soft hands…

Reinforcement Learning

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

2017-09-28 · Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani 외

Dexterous multi-fingered hands are extremely versatile and provide a generic way to perform a multitude of tasks in human-centric environments. However, effectively controlling them remains challenging due to their high …

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Learning Dexterous In-Hand Manipulation

2018-08-01 · OpenAI, Marcin Andrychowicz, Bowen Baker, Maciek Chociej 외

We use reinforcement learning (RL) to learn dexterous in-hand manipulation policies which can perform vision-based object reorientation on a physical Shadow Dexterous Hand. The training is performed in a simulated enviro…

Friction reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)