Reinforcement learning in robotic applications: a comprehensive survey
In recent trends, artificial intelligence (AI) is used for the creation of complex automated
control systems. Still, researchers are trying to make a completely autonomous system that …
control systems. Still, researchers are trying to make a completely autonomous system that …
Dynamic movement primitives in robotics: A tutorial survey
Biological systems, including human beings, have the innate ability to perform complex
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …
A DMPs-based framework for robot learning and generalization of humanlike variable impedance skills
One promising approach for robots efficiently learning skills is to learn manipulation skills
from human tutors by demonstration and then generalize these learned skills to complete …
from human tutors by demonstration and then generalize these learned skills to complete …
Path integral guided policy search
We present a policy search method for learning complex feedback control policies that map
from high-dimensional sensory inputs to motor torques, for manipulation tasks with …
from high-dimensional sensory inputs to motor torques, for manipulation tasks with …
Optimized assistive human–robot interaction using reinforcement learning
An intelligent human-robot interaction (HRI) system with adjustable robot behavior is
presented. The proposed HRI system assists the human operator to perform a given task …
presented. The proposed HRI system assists the human operator to perform a given task …
Learning variable impedance control for contact sensitive tasks
Reinforcement learning algorithms have shown great success in solving different problems
ranging from playing video games to robotics. However, they struggle to solve delicate …
ranging from playing video games to robotics. However, they struggle to solve delicate …
[HTML][HTML] Robust quadruped jum** via deep reinforcement learning
In this paper, we consider a general task of jum** varying distances and heights for a
quadrupedal robot in noisy environments, such as off of uneven terrain and with variable …
quadrupedal robot in noisy environments, such as off of uneven terrain and with variable …
Impedance variation and learning strategies in human–robot interaction
In this survey, various concepts and methodologies developed over the past two decades for
varying and learning the impedance or admittance of robotic systems that physically interact …
varying and learning the impedance or admittance of robotic systems that physically interact …
Robust high-speed running for quadruped robots via deep reinforcement learning
Deep reinforcement learning has emerged as a popular and powerful way to develop
locomotion controllers for quadruped robots. Common approaches have largely focused on …
locomotion controllers for quadruped robots. Common approaches have largely focused on …
Learning potential functions from human demonstrations with encapsulated dynamic and compliant behaviors
We consider the problem of devising a unified control policy capable of regulating both the
robot motion and its physical interaction with the environment. We formulate this control …
robot motion and its physical interaction with the environment. We formulate this control …