Training (meteorology)
Related papers: 20
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Training, in the context of robotics and AI, refers to the process by which a system learns to perform tasks by exposure to data, simulated environments, or iterative feedback. Rather than being explicitly programmed with rules, a robot or AI agent adjusts its internal parameters — such as neural network weights — based on experience, reward signals, or demonstration. Training methods range from supervised learning on labeled datasets to reinforcement learning in simulation, where agents practice millions of trials before deployment on physical hardware. Techniques like sim-to-real transfer and dynamics randomization help bridge the gap between simulated training environments and real-world conditions. In rehabilitation robotics, training also describes structured therapeutic regimens where robotic devices guide patients through repetitive movements to restore motor function after stroke or spinal cord injury. The importance of training cannot be overstated: it is the fundamental mechanism that enables robots to acquire perception, motor control, and decision-making capabilities, making the difference between brittle, hand-coded behavior and flexible, adaptive performance across diverse real-world scenarios.
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel
Citations: 1715 • 2016
End-to-End Training of Deep Visuomotor Policies
Sergey Levine, Chelsea Finn, Trevor Darrell, Pieter Abbeel
Citations: 1399 • 2015
Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
Citations: 787 • 2018
Electromechanical-assisted training for walking after stroke
Jan Mehrholz, Simone Thomas, Joachim Kügler, Marcus Pohl, Bernhard Elsner
Citations: 566 • 2017
Using Machine Teaching to Identify Optimal Training-Set Attacks on Machine Learners
Shike Mei, Xiaojin Zhu
Citations: 368 • 2015
Effects of Training With a Robot-Virtual Reality System Compared With a Robot Alone on the Gait of Individuals After Stroke
Anat Mirelman, Paolo Bonato, Judith E. Deutsch
Citations: 329 • 2008
Robot-Assisted Adaptive Training: Custom Force Fields for Teaching Movement Patterns
James L. Patton, Ferdinando A. Mussa-Ivaldi
Citations: 268 • 2004
Resting State Changes in Functional Connectivity Correlate With Movement Recovery for BCI and Robot-Assisted Upper-Extremity Training After Stroke
Bálint Várkuti, Cuntai Guan, Yaozhang Pan, Kok Soon Phua, Kai Keng Ang, Christopher Wee Keong Kuah, Karen Sui Geok Chua, Beng Ti Ang, Niels Birbaumer, Ranganatha Sitaram
Citations: 263 • 2012
Training and learning robotic surgery, time for a more structured approach: a systematic review
HWR Schreuder, Richard G. H. Wolswijk, Ronald P. Zweemer, Marlies P. Schijven, R.H.M. Verheijen
Citations: 225 • 2011
Locomotor Training in Subjects with Sensori‐Motor Deficits: An Overview of the Robotic Gait Orthosis Lokomat
Robert Riener, Lars Lünenburger, Irin C. Maier, Giorgio Colombo, V. Dietz
Citations: 222 • 2010
A comprehensive review of robotic surgery curriculum and training for residents, fellows, and postgraduate surgical education
Richard J. Chen, Priscila Rodrígues Armijo, Crystal Krause, Ka‐Chun Siu, Dmitry Oleynikov
Citations: 216 • 2019
Comparison of Two Techniques of Robot-Aided Upper Limb Exercise Training After Stroke
Joel Stein, Hermano Igo Krebs, Walter R. Frontera, Susan E. Fasoli, Richard L. Hughes, Neville Hogan
Citations: 206 • 2004
Training in Robotic Surgery—an Overview
Ashwin Sridhar, T. Briggs, John D. Kelly, Senthil Nathan
Citations: 205 • 2017
Effectiveness of VR-based training on improving construction workers’ knowledge, skills, and safety behavior in robotic teleoperation
Pooya Adami, Patrick Borges Rodrigues, Peter J. Woods, Burçin Becerik-Gerber, Lúcio Soibelman, Yasemin Copur‐Gencturk, Gale Lucas
Citations: 202 • 2021
Virtual reality training for the operating room and cardiac catheterisation laboratory
Anthony G. Gallagher, Christopher U. Cates
Citations: 197 • 2004
Training and exercise to drive poststroke recovery
Bruce H. Dobkin
Citations: 191 • 2008
Gait training after spinal cord injury: safety, feasibility and gait function following 8 weeks of training with the exoskeletons from Ekso Bionics
Carsten Bach Baunsgaard, Ulla Vig Nissen, Anne K. Brust, Angela Frotzler, Cornelia Ribeill, Yorck-Bernhard Kalke, Natacha León, Belén Gómez, Kersti Samuelsson, Wolfram Antepohl, Ulrika Holmström, Niklas Marklund, Thomas Glott, Arve Opheim, Jesús Benito, Narda Murillo, Janneke Nachtegaal, Willemijn Faber, Fin Biering‐Sørensen
Citations: 180 • 2017
Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion
Gwanghyeon Ji, Juhyeok Mun, Hyeongjun Kim, Jemin Hwangbo
Citations: 179 • 2022
The effect of interactive cognitive-motor training in reducing fall risk in older people: a systematic review
Daniel Schoene, Trinidad Valenzuela, Stephen R. Lord, Eling D. de Bruin
Citations: 176 • 2014
Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training
Alexander Duschau-Wicke, Andrea Caprez, Robert Riener
Citations: 174 • 2010