Stable Motion Primitives via Imitation and Contrastive Learning

Model-Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges

(2023) Cosimo Della Santina et al.   IEEE CONTROL SYSTEMS MAGAZINE

ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

(2023) Ge Li et al.   IEEE Robotics and Automation Letters

Avoiding Dense and Dynamic Obstacles in Enclosed Spaces: Application to Moving in Crowds

(2022) Lukas Huber et al.   IEEE Transactions on Robotics

Constructing Neural Network-Based Models for Simulating Dynamical Systems

(2022) Christian Møldrup Legaard et al.   ACM COMPUTING SURVEYS

Training of deep neural networks for the generation of dynamic movement primitives

(2020) Rok Pahič et al.   NEURAL NETWORKS

Deep Metric Learning: A Survey

(2019) Kaya et al.   Symmetry-Basel

Fast and Stable Learning of Dynamical Systems Based on Extreme Learning Machine

(2017) Jianghua Duan et al.   IEEE Transactions on Systems Man Cybernetics-Systems

Fast diffeomorphic matching to learn globally asymptotically stable nonlinear dynamical systems

(2016) Nicolas Perrin et al.   SYSTEMS & CONTROL LETTERS

Learning robot motions with stable dynamical systems under diffeomorphic transformations

(2015) Klaus Neumann et al.   ROBOTICS AND AUTONOMOUS SYSTEMS

Neural learning of vector fields for encoding stable dynamical systems

(2014) A. Lemme et al.   NEUROCOMPUTING

Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motions

(2014) S. Mohammad Khansari-Zadeh et al.   ROBOTICS AND AUTONOMOUS SYSTEMS

A dynamical system approach to realtime obstacle avoidance

(2012) Seyed Mohammad Khansari-Zadeh et al.   AUTONOMOUS ROBOTS

Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

(2012) Auke Jan Ijspeert et al.   NEURAL COMPUTATION

Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models

(2011) S. Mohammad Khansari-Zadeh et al.   IEEE Transactions on Robotics