Movement (music)
Related papers: 20
About
Movement, in the context of robotics and AI, refers to the coordinated, purposeful displacement of a body or mechanism through space and time — encompassing trajectory planning, motor control, execution, and adaptation. Drawing on neuroscience, biomechanics, and control theory, researchers study how biological organisms generate smooth, efficient movement and translate those principles into robotic systems. Techniques such as Dynamic Movement Primitives (DMPs) encode motion as learned differential equations, enabling robots to reproduce, adapt, and generalize demonstrated movements in real time. Movement analysis also informs rehabilitation robotics, where quantitative measures of smoothness, variability, and coordination guide robot-assisted therapy following stroke or neurological injury. Understanding variability through nonlinear dynamics reveals whether movement patterns reflect healthy adaptability or pathological dysfunction. Movement matters because it bridges perception and action: whether enabling a humanoid robot to imitate human gestures, training a prosthetic limb, or designing socially expressive robots, the quality and naturalness of movement directly determines how effectively autonomous systems interact with the physical world and with people.
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Top Cited Papers
Real-time prediction of hand trajectory by ensembles of cortical neurons in primates
Johan Wessberg, Christopher R. Stambaugh, Jerald D. Kralik, Pamela D. Beck, Mark Laubach, John K. Chapin, Jung Kim, Sean Biggs, Mandayam A. Srinivasan, Miguel A. L. Nicolelis
Citations: 1495 • 2000
OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement
Ajay Seth, Jennifer L. Hicks, Thomas K. Uchida, Ayman Habib, Christopher L. Dembia, James J. Dunne, Carmichael Ong, Matthew S. DeMers, Apoorva Rajagopal, Matthew Millard, Samuel R. Hamner, Edith M. Arnold, Jennifer R. Yong, Shrinidhi Kowshika Lakshmikanth, Michael Sherman, Joy P. Ku, Scott L. Delp
Citations: 1326 • 2018
Human movement variability, nonlinear dynamics, and pathology: Is there a connection?
Nicholas Stergiou, Leslie M. Decker
Citations: 1050 • 2011
Movement imitation with nonlinear dynamical systems in humanoid robots
Auke Jan Ijspeert, Jun Nakanishi, Stefan Schaal
Citations: 842 • 2003
An Interference Effect of Observed Biological Movement on Action
James M. Kilner, Yves Paulignan, Sarah‐Jayne Blakemore
Citations: 841 • 2003
Movement Smoothness Changes during Stroke Recovery
Brandon Rohrer, Susan E. Fasoli, Hermano Igo Krebs, Richard L. Hughes, Bruce T. Volpe, Walter R. Frontera, Joel Stein, Neville Hogan
Citations: 777 • 2002
Learning and generalization of motor skills by learning from demonstration
Peter Pástor, H. Hoffmann, Tamim Asfour, Stefan Schaal
Citations: 710 • 2009
Qualitative changes of spontaneous movements in fetus and preterm infant are a marker of neurological dysfunction
H.F.R. Prechtl
Citations: 604 • 1990
Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics
Stefan Schaal
Citations: 602 • 2006
The cerebellum is involved in predicting the sensory consequences of action
Sarah‐Jayne Blakemore, Chris Frith, Daniel M. Wolpert
Citations: 597 • 2001
Movement Variability and the Use of Nonlinear Tools: Principles to Guide Physical Therapist Practice
Regina T. Harbourne, Nicholas Stergiou
Citations: 519 • 2009
What mechanisms coordinate leg movement in walking arthropods?
Holk Cruse
Citations: 454 • 1990
Persistence of Motor Adaptation During Constrained, Multi-Joint, Arm Movements
Robert A. Scheidt, David J. Reinkensmeyer, Michael A. Conditt, William Z. Rymer, Ferdinando A. Mussa-Ivaldi
Citations: 425 • 2000
Probabilistic Movement Primitives
Alexandros Paraschos, Christian Daniel, Jan Peters, Gerhard Neumann
Citations: 413 • 2013
Motor Learning by Observing
Andrew A. G. Mattar, Paul L. Gribble
Citations: 410 • 2005
Learning from demonstration and adaptation of biped locomotion
Jun Nakanishi, Jun Morimoto, Gen Endo, Gordon Cheng, Stefan Schaal, Mitsuo Kawato
Citations: 400 • 2004
Hierarchical neural network model for voluntary movement with application to robotics
Mitsuo Kawato, Y. Uno, M. Isobe, Ryoji Suzuki
Citations: 392 • 1988
Predicting the Consequences of Our Own Actions: The Role of Sensorimotor Context Estimation
Sarah‐Jayne Blakemore, Susan J. Goodbody, Daniel M. Wolpert
Citations: 384 • 1998
Motions or muscles? Some behavioral factors underlying robotic assistance of motor recovery
Neville Hogan, Hermano Igo Krebs, Brandon Rohrer, Jerome J. Palazzolo, Laura Dipietro, Susan E. Fasoli, Joel Stein, Walter R. Frontera, Daniel Lynch, Bruce T. Volpe
Citations: 374 • 2006
Automating Arm Movement Training Following Severe Stroke: Functional Exercises With Quantitative Feedback in a Gravity-Reduced Environment
Robert J. Sanchez, Jinzhi Liu, Stephen M. Rao, Purva Shah, Richard A. Smith, Tariq Rahman, Steven C. Cramer, J.E. Bobrow, David J. Reinkensmeyer
Citations: 358 • 2006