Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors
École Polytechnique Fédérale de Lausanne · University of Edinburgh · +3 more institutions
Abstract
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…
Citation impact
- FWCI
- 41.51
- Percentile
- 100%
- References
- 142
Authors
5- AJAuke Jan IjspeertCorresponding
École Polytechnique Fédérale de Lausanne
- JNJun NakanishiCorresponding
University of Edinburgh
- HHH. HoffmannCorresponding
University of Southern California
- PPPeter PástorCorresponding
University of Southern California
- SSStefan SchaalCorresponding
University of Southern California, Advanced Telecommunications Research Institute International, Max Planck Institute for Intelligent Systems
Topics & keywords
- Attractor
- Dynamical systems theory
- Nonlinear system
- Artificial intelligence
- Computer science
- Robotics
- Limit cycle
- Dynamical system (definition)