Obstacles and opportunities for learning from demonstration in practical industrial assembly: A systematic literature review
VH Moreno, S Jansing, M Polikarpov… - Robotics and Computer …, 2024 - Elsevier
Learning from demonstration is one of the most promising methods to counteract the
challenging long-term trends in repetitive industrial assembly. It offers not only a …
challenging long-term trends in repetitive industrial assembly. It offers not only a …
A neural network based framework for variable impedance skills learning from demonstrations
Robots are becoming standard collaborators not only in factories, hospitals, and offices, but
also in people's homes, where they can play an important role in situations where a human …
also in people's homes, where they can play an important role in situations where a human …
Learning from demonstration for autonomous generation of robotic trajectory: Status quo and forward-looking overview
Learning from demonstration (LfD) enables robots to intuitively acquire new skills from
human demonstrations and incrementally evolve robotic intelligence. Given the significance …
human demonstrations and incrementally evolve robotic intelligence. Given the significance …
Learning Riemannian stable dynamical systems via diffeomorphisms
J Zhang, HB Mohammadi, L Rozo - 6th Annual Conference on …, 2022 - openreview.net
Dexterous and autonomous robots should be capable of executing elaborated dynamical
motions skillfully. Learning techniques may be leveraged to build models of such dynamic …
motions skillfully. Learning techniques may be leveraged to build models of such dynamic …
[HTML][HTML] Kinesthetic learning based on fast marching square method for manipulation
The advancement of robotics in recent years has driven the growth of robotic applications for
more complex tasks requiring manipulation capabilities. Recent works have focused on …
more complex tasks requiring manipulation capabilities. Recent works have focused on …
Learning robust point-to-point motions adversarially: A stochastic differential equation approach
This letter proposes a robust stochastic differential equation approach for learning point-to-
point motions in an adversarial way. The proposed stochastic dynamical model combines …
point motions in an adversarial way. The proposed stochastic dynamical model combines …
Unraveling the single tangent space fallacy: An analysis and clarification for applying Riemannian geometry in robot learning
In the realm of robotics, numerous downstream robotics tasks leverage machine learning
methods for processing, modeling, or synthesizing data. Often, this data comprises variables …
methods for processing, modeling, or synthesizing data. Often, this data comprises variables …
Mapless navigation for UAVs via reinforcement learning from demonstrations
This paper is concerned with the problems of mapless navigation for unmanned aerial
vehicles in the scenarios with limited sensor accuracy and computing capability. A novel …
vehicles in the scenarios with limited sensor accuracy and computing capability. A novel …
Learning a Stable Dynamic System with a Lyapunov Energy Function for Demonstratives Using Neural Networks
Autonomous Dynamic System (DS)-based algorithms hold a pivotal and foundational role in
the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable …
the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable …
Learning English Writing Skills from Images
Learning from Demonstration (LfD) is a widely utilized technology within the realm of
robotics, and the task of writing holds particular significance in this context. Typically …
robotics, and the task of writing holds particular significance in this context. Typically …