225 citations · 284 across the 9 of their papers we have counts for
9 papers
Safe Execution of Learned Orientation Skills with Conic Control Barrier Functions
Zheng Shen, Matteo Saveriano, Fares J. Abu-Dakka +1
In the field of Learning from Demonstration (LfD), Dynamical Systems (DSs) have gained significant attention due to their ability to generate real-time motions and reach predefined…
Orientation Control with Variable Stiffness Dynamical Systems
Youssef Michel, Matteo Saveriano, Fares J. Abu-Dakka +1
Recently, several approaches have attempted to combine motion generation and control in one loop to equip robots with reactive behaviors, that cannot be achieved with traditional t…
Learning Deep Robotic Skills on Riemannian manifolds
Weitao Wang, Matteo Saveriano, Fares J. Abu-Dakka
In this paper, we propose RiemannianFlow, a deep generative model that allows robots to learn complex and stable skills evolving on Riemannian manifolds. Examples of Riemannian dat…
Geometric Reinforcement Learning For Robotic Manipulation
Naseem Alhousani, Matteo Saveriano, Ibrahim Sevinc +3
Reinforcement learning (RL) is a popular technique that allows an agent to learn by trial and error while interacting with a dynamic environment. The traditional Reinforcement Lear…
Learning Stable Robotic Skills on Riemannian Manifolds
Matteo Saveriano, Fares J. Abu-Dakka, Ville Kyrki
In this paper, we propose an approach to learn stable dynamical systems evolving on Riemannian manifolds. The approach leverages a data-efficient procedure to learn a diffeomorphic…
A Unified Formulation of Geometry-aware Dynamic Movement Primitives
Fares J. Abu-Dakka, Matteo Saveriano, Ville Kyrki
Learning from demonstration (LfD) is considered as an efficient way to transfer skills from humans to robots. Traditionally, LfD has been used to transfer Cartesian and joint posit…
Periodic DMP formulation for Quaternion Trajectories
Fares J. Abu-Dakka, Matteo Saveriano, Luka Peternel
Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dynamic movement primitives (DMPs) have been widely exploited as an effective and an…
Dynamic Movement Primitives in Robotics: A Tutorial Survey
Matteo Saveriano, Fares J. Abu-Dakka, Aljaz Kramberger +1
Biological systems, including human beings, have the innate ability to perform complex tasks in versatile and agile manner. Researchers in sensorimotor control have tried to unders…
Variable impedance control and learning -- A review
Fares J. Abu-Dakka, Matteo Saveriano
Robots that physically interact with their surroundings, in order to accomplish some tasks or assist humans in their activities, require to exploit contact forces in a safe and pro…