Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Dynamic pattern recognition of coordinated biological motion
Neural Networks
A Kendama learning robot based on bi-directional theory
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
On contraction analysis for non-linear systems
Automatica (Journal of IFAC)
Modelling and Control of Robot Manipulators
Modelling and Control of Robot Manipulators
Control Systems Design: An Introduction to State-Space Methods
Control Systems Design: An Introduction to State-Space Methods
Using Humanoid Robots to Study Human Behavior
IEEE Intelligent Systems
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Asymptotically Stable Running for a Five-Link, Four-Actuator, Planar Bipedal Robot
International Journal of Robotics Research
Motor primitive and sequence self-organization in a hierarchical recurrent neural network
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Movement Generation with Circuits of Spiking Neurons
Neural Computation
Constructive Incremental Learning from Only Local Information
Neural Computation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Biological Cybernetics - Special Issue: Dynamic Principles
Design of a Central Pattern Generator Using Reservoir Computing for Learning Human Motion
AT-EQUAL '09 Proceedings of the 2009 Advanced Technologies for Enhanced Quality of Life
Learning and generalization of motor skills by learning from demonstration
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Learning motor primitives for robotics
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Task-specific generalization of discrete and periodic dynamic movement primitives
IEEE Transactions on Robotics
Learning Non-linear Multivariate Dynamics of Motion in Robotic Manipulators
International Journal of Robotics Research
A Generalized Path Integral Control Approach to Reinforcement Learning
The Journal of Machine Learning Research
Bio-mimetic trajectory generation of robots via artificial potential field with time base generator
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Robotics
From dynamic movement primitives to associative skill memories
Robotics and Autonomous Systems
Hi-index | 0.00 |
Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior e.g., stable locomotion from a system of coupled oscillators under perceptual guidance. Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system, such as a set of linear differential equations, and transform those into a weakly nonlinear system with prescribed attractor dynamics by means of a learnable autonomous forcing term. Both point attractors and limit cycle attractors of almost arbitrary complexity can be generated. We explain the design principle of our approach and evaluate its properties in several example applications in motor control and robotics.