ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

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

(2020) Rok Pahič et al.   NEURAL NETWORKS

Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives

(2018) Chenguang Yang et al.   IEEE Transactions on Neural Networks and Learning Systems

Phase estimation for fast action recognition and trajectory generation in human–robot collaboration

(2017) Guilherme Maeda et al.   INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH

Probabilistic movement primitives for coordination of multiple human–robot collaborative tasks

(2016) Guilherme J. Maeda et al.   AUTONOMOUS ROBOTS

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

Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

(2012) Auke Jan Ijspeert et al.   NEURAL COMPUTATION