Recent advances in robot learning from demonstration
H Ravichandar, AS Polydoros… - Annual review of …, 2020 - annualreviews.org
In the context of robotics and automation, learning from demonstration (LfD) is the paradigm
in which robots acquire new skills by learning to imitate an expert. The choice of LfD over …
in which robots acquire new skills by learning to imitate an expert. The choice of LfD over …
Learning for a robot: Deep reinforcement learning, imitation learning, transfer learning
J Hua, L Zeng, G Li, Z Ju - Sensors, 2021 - mdpi.com
Dexterous manipulation of the robot is an important part of realizing intelligence, but
manipulators can only perform simple tasks such as sorting and packing in a structured …
manipulators can only perform simple tasks such as sorting and packing in a structured …
What matters in learning from offline human demonstrations for robot manipulation
Imitating human demonstrations is a promising approach to endow robots with various
manipulation capabilities. While recent advances have been made in imitation learning and …
manipulation capabilities. While recent advances have been made in imitation learning and …
An algorithmic perspective on imitation learning
As robots and other intelligent agents move from simple environments and problems to more
complex, unstructured settings, manually programming their behavior has become …
complex, unstructured settings, manually programming their behavior has become …
Mimicplay: Long-horizon imitation learning by watching human play
Imitation learning from human demonstrations is a promising paradigm for teaching robots
manipulation skills in the real world. However, learning complex long-horizon tasks often …
manipulation skills in the real world. However, learning complex long-horizon tasks often …
Progress and prospects of the human–robot collaboration
Recent technological advances in hardware design of the robotic platforms enabled the
implementation of various control modalities for improved interactions with humans and …
implementation of various control modalities for improved interactions with humans and …
Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
Imitation learning is a powerful paradigm for robot skill acquisition. However, obtaining
demonstrations suitable for learning a policy that maps from raw pixels to actions can be …
demonstrations suitable for learning a policy that maps from raw pixels to actions can be …
A survey of inverse reinforcement learning
Learning from demonstration, or imitation learning, is the process of learning to act in an
environment from examples provided by a teacher. Inverse reinforcement learning (IRL) is a …
environment from examples provided by a teacher. Inverse reinforcement learning (IRL) is a …
Motion planning networks
Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics
applications such as self-driving cars. Existing motion planning methods become ineffective …
applications such as self-driving cars. Existing motion planning methods become ineffective …
A tutorial on task-parameterized movement learning and retrieval
S Calinon - Intelligent service robotics, 2016 - Springer
Task-parameterized models of movements aim at automatically adapting movements to new
situations encountered by a robot. The task parameters can, for example, take the form of …
situations encountered by a robot. The task parameters can, for example, take the form of …