Peg-in-hole assembly skill imitation learning method based on ProMPs under task geometric representation
Y Zang, P Wang, F Zha, W Guo, C Zheng… - Frontiers in …, 2023 - frontiersin.org
Introduction Behavioral Cloning (BC) is a common imitation learning method which utilizes
neural networks to approximate the demonstration action samples for task manipulation skill …
neural networks to approximate the demonstration action samples for task manipulation skill …
Robot learning of assistive manipulation tasks by demonstration via head gesture-based interface
M Kyrarini, Q Zheng, MA Haseeb… - 2019 IEEE 16th …, 2019 - ieeexplore.ieee.org
Assistive robotic manipulators have the potential to support the lives of people suffering from
severe motor impairments. They can support individuals with disabilities to independently …
severe motor impairments. They can support individuals with disabilities to independently …
A Variable Impedance Skill Learning Algorithm Based on Kernelized Movement Primitives
This article proposes a novel learning from demonstrations (LfD) method based on
kernelized movement primitives (KMP). The original KMP algorithm is excellent at …
kernelized movement primitives (KMP). The original KMP algorithm is excellent at …
Non-parametric Gaussian process movement primitive with via-point constraint for effective and safe robot skill learning
Learning from demonstration (LFD) algorithms has been proven to be an effective way to
encode basic human skills, such as probabilistic movement primitives (ProMPs). However …
encode basic human skills, such as probabilistic movement primitives (ProMPs). However …
[图书][B] Robot Learning Human Skills and Intelligent Control Design
C Yang, C Zeng, J Zhang - 2021 - taylorfrancis.com
In the last decades robots are expected to be of increasing intelligence to deal with a large
range of tasks. Especially, robots are supposed to be able to learn manipulation skills from …
range of tasks. Especially, robots are supposed to be able to learn manipulation skills from …
Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planning
Reinforcement learning (RL) for motion planning of multi-degree-of-freedom robots still
suffers from low efficiency in terms of slow training speed and poor generalizability. In this …
suffers from low efficiency in terms of slow training speed and poor generalizability. In this …
The arm planning with dynamic movement primitive for humanoid service robot
M Lin, Z Lu, S Wang, R Wang - 2020 5th International …, 2020 - ieeexplore.ieee.org
In order to realize the autonomous motor learning skills of humanoid service robot, we
propose a systematic framework for trajectory planning and learning of robotic arms in this …
propose a systematic framework for trajectory planning and learning of robotic arms in this …
Robot Learning from Multiple Demonstrations Based on Generalized Gaussian Mixture Model
The quality of skills learned by robots from demonstrations depends on the level of
demonstration by the instructor, while models such as Dynamic Motion Primitives (DMP) are …
demonstration by the instructor, while models such as Dynamic Motion Primitives (DMP) are …
Learning to optimize control policies and evaluate reproduction performance from human demonstrations
We are interested in learning from demonstration (LfD) that can both learn and execute a
trajectory and evaluate the quality of a previously unseen trajectory in the domain of …
trajectory and evaluate the quality of a previously unseen trajectory in the domain of …
Robot Learning from Human Demonstrations for Human-Robot Synergy
M Kyrarini - 2019 - media.suub.uni-bremen.de
Human-robot synergy enables new developments in industrial and assistive robotics
research. In recent years, collaborative robots can work together with humans to perform a …
research. In recent years, collaborative robots can work together with humans to perform a …