Learning and generalization of motor skills by learning from demonstration

Is imitation learning the route to humanoid robots?

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Movement imitation with nonlinear dynamical systems in humanoid robots

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Robot learning from demonstration

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Computational approaches to motor learning by imitation

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Imitation in Animals and Artifacts

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Operational Space Control: A Theoretical and Empirical Comparison

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Biologically-inspired dynamical systems for movement generation: Automatic real-time goal adaptation and obstacle avoidance

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Closed-loop manipulator control using quaternion feedback

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A Latent State-Based Multimodal Execution Monitor with Anomaly Detection and Classification for Robot Introspection

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Learning and Generalizing Cooperative Manipulation Skills Using Parametric Dynamic Movement Primitives

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Learning Skills From Demonstrations: A Trend From Motion Primitives to Experience Abstraction

Tavassoli, M., Katyara, S., Pozzi, M., Deshpande, N., Caldwell, D. G., & Prattichizzo, D. (2023) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2023.3296166 · Cited by 24

Topological trajectory clustering with relative persistent homology

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An extended DMP framework for robot learning and improving variable stiffness manipulation

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Learning a Set of Interrelated Tasks by Using a Succession of Motor Policies for a Socially Guided Intrinsically Motivated Learner

Duminy, N., Nguyen, S. M., & Duhaut, D. (2019) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2018.00087 · Cited by 23

A novel human-robot skill transfer method for contact-rich manipulation task

Dong, J., Si, W., & Yang, C. (2023) · Robotic Intelligence and Automation · doi:10.1108/ria-01-2023-0002 · Cited by 23

Cooperation in the Air: A Learning-Based Approach for the Efficient Motion Planning of Aerial Manipulators

Kim, H., Seo, H., Son, C. Y., Lee, H., Kim, S., & Kim, H. J. (2018) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2018.2866766 · Cited by 23

V2CNet: A Deep Learning Framework to Translate Videos to Commands for Robotic ManipulationPreprint

Nguyen, A., Do, T.-T., Reid, I. D., Caldwell, D. G., & Tsagarakis, N. G. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.10869 · Cited by 23

Tac-Man: Tactile-Informed Prior-Free Manipulation of Articulated Objects

Zhao, Z., Li, Y., Li, W., Qi, Z., Ruan, L., Zhu, Y., & Althoefer, K. A. (2024) · IEEE Transactions on Robotics · doi:10.1109/tro.2024.3508134 · Cited by 22

Task-Adaptive Robot Learning From Demonstration With Gaussian Process Models Under Replication

Arduengo, M., Colomé, A., Borràs, J., Sentis, L., & Torras, C. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3056367 · Cited by 22

UserSim: User Simulation via Supervised GenerativeAdversarial Network

Zhao, X., Xia, L., Zou, L.-X., Liu, H., Yin, D.-W., & Tang, J.-L. (2021) · The Web Conference · doi:10.1145/3442381.3450125 · Cited by 33

Learning nonlinear dynamical system for movement primitives

Yin, X., & Chen, Q. (2014) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2014.6974516 · Cited by 22

Learning manipulation actions from human demonstrations

Welschehold, T., Dornhege, C., & Burgard, W. (2016) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759555 · Cited by 22

Using dVRK teleoperation to facilitate deep learning of automation tasks for an industrial robot

Liang, J., Mahler, J., Laskey, M., Li, P., & Goldberg, K. Y. (2017) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/coase.2017.8256067 · Cited by 22

Learning hand movements from markerless demonstrations for humanoid tasks

Mao, R., Yang, Y., Fermuller, C. M., Aloimonos, Y., & Baras, J. S. (2014) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids.2014.7041476 · Cited by 21

An Intervention-AUV learns how to perform an underwater valve turning

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ControlIt! — A Software Framework for Whole-Body Operational Space Control

Fok, C., Johnson, G., Yamokoski, J. D., Mok, A. K., & Sentis, L. (2015) · International Journal of Humanoid Robotics · doi:10.1142/s0219843615500401 · Cited by 21

Gaussian-process-based robot learning from demonstration

Arduengo, M., Colomé, A., Lobo-Prat, J., Sentis, L., & Carme Torras, A. (2023) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-023-04551-7 · Cited by 21

SQUIRL: Robust and Efficient Learning from Video Demonstration of Long-Horizon Robotic Manipulation Tasks

Wu, B., Xu, F., He, Z., Gupta, A., & Allen, P. K. (2020) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9340915 · Cited by 21

Trajectory-Based Skill Learning for Overhead Construction Robots Using Generalized Cylinders with Orientation

Liang, C., Kamat, V. R., Menassa, C. C., & McGee, W. (2021) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0001004 · Cited by 23

A Motion Capture and Imitation Learning Based Approach to Robot Control

Racinskis, P., Ārents, J., & Greitāns, M. (2022) · Applied Sciences · doi:10.3390/app12147186 · Cited by 24

Combination of Dynamical Movement Primitives With Trajectory Segmentation and Node Mapping for Robot Machining Motion Learning

Zhou, P., Zhao, X., Tao, B., & Ding, H. (2022) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2022.3196036 · Cited by 21

Human-robot interaction for learning and adaptation of object movements

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LAT: A simple Learning from Demonstration method

Reiner, B., Ertel, W., Posenauer, H., & Schneider, M. (2014) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2014.6943190 · Cited by 21

Towards Learning of Generic Skills for Robotic Manipulation

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Human-Guided Object Mapping for Task Transfer

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A Reversible Dynamic Movement Primitive formulation

Sidiropoulos, A., & Doulgeri, Z. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9562059 · Cited by 21

Motion planning and reactive control on learnt skill manifolds

Havoutis, I., & Ramamoorthy, S. (2013) · The International Journal of Robotics Research · doi:10.1177/0278364913482016 · Cited by 21

Mirroring without Overimitation: Learning Functionally Equivalent Manipulation Actions

Liu, H., Zhang, C., Zhu, Y., Jiang, C., & Zhu, S. C. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33018025 · Cited by 23

One-shot robot programming by demonstration using an online oriented particles simulation

Groth, C., & Henrich, D. (2014) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio.2014.7090323 · Cited by 20

Demonstration-Guided Pose Planning and Tracking for Multi-Section Continuum Robots Considering Robot Dynamics

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Robot tool use: A survey

Qin, M., Brawer, J., & Scassellati, B. M. (2023) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.1009488 · Cited by 20

Learning multiple strategies to perform a valve turning with underwater currents using an I-AUV

Carrera, A., Palomeras, N., Hurtós, N., Kormushev, P. S., & Carreras, M. (2015) · MTS/IEEE OCEANS Conference (OCEANS) · doi:10.1109/oceans-genova.2015.7271609 · Cited by 20

A Constraint-Aware Motion Planning Algorithm for Robotic Folding of Clothes

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Teaching robots the use of human tools from demonstration with non-dexterous end-effectors

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Multi-Modal Robot Apprenticeship: Imitation Learning Using Linearly Decayed DMP+ in a Human-Robot Dialogue System

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Robot Choreography: The Use of the Kinetography Laban System to Notate Robot Action and Motion

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Data-Driven Robotic Manipulation of Cloth-like Deformable Objects: The Present, Challenges and Future Prospects

Kadi, H. A., & Terzić, K. (2023) · Sensors · doi:10.3390/s23052389 · Cited by 27

Robot learning from multiple demonstrations with dynamic movement primitive

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A Comprehensive Study on Robot Learning from Demonstration

Ambhore, S. (2020) · International Conference on Innovative Mechanisms for Industry Applications · doi:10.1109/icimia48430.2020.9074946 · Cited by 19

Intent-Aware Predictive Haptic Guidance and its Application to Shared Control Teleoperation

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Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models

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Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

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Learning Action Primitives

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Toward Simulating Environments in Reinforcement Learning Based RecommendationsPreprint

Zhao, X., Xia, L., Ding, Z.-Y., Yin, D.-W., & Tang, J.-L. (2019) · arXiv.org · doi:10.48550/arxiv.1906.11462 · Cited by 26

Periodic DMP formulation for Quaternion Trajectories

Abu‐Dakka, F. J., Saveriano, M., & Peternel, L. (2021) · International Conference on Advanced Robotics (ICAR) · doi:10.1109/icar53236.2021.9659319 · Cited by 18

Coupling Mobile Base and End-Effector Motion in Task Space

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Dynamic optimality in real-time: A learning framework for near-optimal robot motions

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Usability of force-based controllers in physical human-robot interaction

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A Probabilistic Representation for Dynamic Movement PrimitivesPreprint

Meier, F., & Stefan Schaal, A. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.05932 · Cited by 18

Hierarchical Neural Dynamic Policies

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Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward‐based tasks

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The BesMan Learning Platform for Automated Robot Skill Learning

Gutzeit, L., Fabisch, A., Otto, M., Metzen, J. H., Hansen, J. M., Kirchner, F., & Kirchner, E. A. (2018) · Frontiers in Robotics and AI · doi:10.3389/frobt.2018.00043 · Cited by 18

Learning Task Constraints from Demonstration for Hybrid Force/Position Control

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Learning and Generalization of Dynamic Movement Primitives by Hierarchical Deep Reinforcement Learning from Demonstration

Kim, W., Lee, C., & Kim, H. (2018) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2018.8594476 · Cited by 18

iRoPro: An interactive Robot Programming Framework

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Multi-Channel Interactive Reinforcement Learning for Sequential Tasks

Koert, D., Kircher, M., Salikutluk, V., D’Eramo, C., & Peters, J. (2020) · Frontiers in Robotics and AI · doi:10.3389/frobt.2020.00097 · Cited by 17

Learning of Planning Models for Dexterous Manipulation Based on Human Demonstrations

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Robotic cloth manipulation for clothing assistance task using Dynamic Movement Primitives

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Constrained-Space Optimization and Reinforcement Learning for Complex Tasks

Tsai, Y.-Y., Xiao, B. J., Johns, E., & Yang, G. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2965392 · Cited by 18

A Practical Roadmap to Learning from Demonstration for Robotic Manipulators in Manufacturing

Barekatain, A., Habibi, H., & Voos, H. (2024) · Robotics · doi:10.3390/robotics13070100 · Cited by 16

Intent inference in shared-control teleoperation system in consideration of user behavior

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Fuzzy dynamical system for robot learning motion skills from human demonstration

Teng, T., Gatti, M., Poni, S., Caldwell, D. G., & Chen, F. (2023) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2023.104406 · Cited by 16

STAP: Sequencing Task-Agnostic Policies

Agia, C., Migimatsu, T., Wu, J., & Bohg, J. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10160220 · Cited by 16

Spatial adaption of robot trajectories based on laplacian trajectory editing

Nierhoff, T., Hirche, S., & Nakamura, Y. (2015) · Autonomous Robots · doi:10.1007/s10514-015-9442-3 · Cited by 16

Autonomous movement generation for manipulators with multiple simultaneous constraints using the attractor dynamics approach

Reimann, H., Iossifidis, I., & Schöner, G. (2011) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2011.5980184 · Cited by 16

Sparse Control for Dynamic Movement Primitives

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Skill Acquisition via Automated Multi-Coordinate Cost Balancing

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Combined Task and Action Learning from Human Demonstrations for Mobile Manipulation Applications

Welschehold, T., Abdo, N., Dornhege, C., & Burgard, W. (2019) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros40897.2019.8968091 · Cited by 16

A Robot 3C Assembly Skill Learning Method by Intuitive Human Assembly Demonstration

Cao, Z., Hu, H., Yang, X., & Lou, Y. (2019) · WRC Symposium on Advanced Robotics and Automation (WRC SARA) · doi:10.1109/wrc-sara.2019.8931930 · Cited by 16

Reinforcement Learning with Dynamic Movement Primitives for Obstacle Avoidance

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Learning Social Affordances and Using Them for Planning

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Learning from Demonstration facilitates Human-Robot Collaborative task execution

Koskinopoulou, M., Piperakis, S., & Trahanias, P. E. (2016) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1109/hri.2016.7451734 · Cited by 16

Learning From Demonstration Based on Environmental Constraints

Li, X., & Brock, O. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3196096 · Cited by 15

Kinesthetic Learning Based on Fast Marching Square Method for Manipulation

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Learning to Plan for Constrained Manipulation from Demonstrations

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Learning Affordance Space in Physical World for Vision-based Robotic Object Manipulation

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Mobile robots path planning based on dynamic movement primitives library

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Robot Programming without Coding

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Cognitive system for autonomous underwater intervention

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Understanding haptics by evolving mechatronic systems

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Learning object, grasping and manipulation activities using hierarchical HMMs

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Bilateral physical interaction with a robot manipulator through a weighted combination of flow fields

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Deep Reinforcement Learning for Contact-Rich Skills Using Compliant Movement PrimitivesPreprint

Spector, O., & Zacksenhouse, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.13223 · Cited by 19

User intent estimation during robot learning using physical human robot interaction primitives

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A Framework for Composite Layup Skill Learning and Generalizing Through Teleoperation

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Representation and generalization of bi-manual skills from kinesthetic teaching

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Towards a unifying grasp representation for imitation learning on humanoid robots

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Learning from Demonstration Facilitates Human-Robot Collaborative Task Execution

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Motion Planning for Continuum Robots: A Learning from Demonstration Approach

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Learning Manipulation Trajectories Using Recurrent Neural NetworksPreprint

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AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at ScalePreprint

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Efficient policy search in low-dimensional embedding spaces by generalizing motion primitives with a parameterized skill memory

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Discovery and recognition of motion primitives in human activities

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An RRT-based path planner for use in trajectory imitation

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