Learning and generalization of motor skills by learning from demonstration

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Robot learning from demonstration

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Learning Attractor Landscapes for Learning Motor Primitives

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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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Movement reproduction and obstacle avoidance with dynamic movement primitives and potential fields

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Control, Planning, Learning, and Imitation with Dynamic Movement Primitives

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Object Action Complexes as an Interface for Planning and Robot Control

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Perceiving Objects and Movements to Generate Actions on a Humanoid Robot

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Experimental Evaluation of Task Space Position/Orientation Control Towards Compliant Control for Humanoid Robots

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End-to-end training of deep visuomotor policies

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Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

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Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates

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End-to-End Training of Deep Visuomotor PoliciesPreprint

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Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models

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Recent Advances in Robot Learning from Demonstration

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Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

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Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation

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Time-Contrastive Networks: Self-Supervised Learning from Video

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Deep spatial autoencoders for visuomotor learning

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Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search

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How is a motor skill learned? Change and invariance at the levels of task success and trajectory control

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An algorithmic perspective on imitation learning

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An Algorithmic Perspective on Imitation Learning

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Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives

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Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives

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One-Shot Visual Imitation Learning via Meta-Learning

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One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning

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Learning contact-rich manipulation skills with guided policy search

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Dynamic movement primitives in robotics: A tutorial survey

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Robot Learning from Demonstration in Robotic Assembly: A Survey

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Trajectories and keyframes for kinesthetic teaching

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Online movement adaptation based on previous sensor experiences

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Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-to-End Learning from Demonstration

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Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories

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Optimal control with learned local models: Application to dexterous manipulation

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Using probabilistic movement primitives in robotics

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Skill learning and task outcome prediction for manipulation

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Keyframe-based Learning from Demonstration

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Learning Latent Plans from PlayPreprint

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Composable Deep Reinforcement Learning for Robotic Manipulation

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Survey of imitation learning for robotic manipulation

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Learning grounded finite-state representations from unstructured demonstrations

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Robot Learning from Human Teachers

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Learning and generalization of complex tasks from unstructured demonstrations

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BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning

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Reinforcement learning to adjust parametrized motor primitives to new situations

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Learning Robotic Assembly from CAD

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Joining Movement Sequences: Modified Dynamic Movement Primitives for Robotics Applications Exemplified on Handwriting

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Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement LearningPreprint

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End-to-End Driving Via Conditional Imitation Learning

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Robot learning of industrial assembly task via human demonstrations

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A Framework for Robot Manipulation: Skill Formalism, Meta Learning and Adaptive Control

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Few-Shot Human Motion Prediction via Meta-learning

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Path integral guided policy search

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Adapting Deep Visuomotor Representations with Weak Pairwise Constraints

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Coarse-to-Fine Imitation Learning: Robot Manipulation from a Single Demonstration

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Robot Learning from Human Teachers

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Learning Non-linear Multivariate Dynamics of Motion in Robotic Manipulators

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Learning motor skills: from algorithms to robot experiments

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Biologically Inspired Motion Modeling and Neural Control for Robot Learning From Demonstrations

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Inverse optimal control for deterministic continuous-time nonlinear systems

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On-line motion synthesis and adaptation using a trajectory database

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A Divergence Minimization Perspective on Imitation Learning MethodsPreprint

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Learning parametric dynamic movement primitives from multiple demonstrations

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Towards Associative Skill Memories

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Skill transfer learning for autonomous robots and human–robot cooperation: A survey

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Learning to pour with a robot arm combining goal and shape learning for dynamic movement primitives

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GELLO: A General, Low-Cost, and Intuitive Teleoperation Framework for Robot Manipulators

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Incremental Semantically Grounded Learning from Demonstration

Niekum, S., Chitta, S., Barto, A. G., Marthi, B., & Osentoski, S. (2013) · Robotics: Science and Systems · doi:10.15607/rss.2013.ix.048 · Cited by 97 · see citing works

A biomimetic approach to inverse kinematics for a redundant robot arm

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Untitled work

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Passive Interaction Control With Dynamical Systems

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Human-to-Robot Imitation in the Wild

Bahl, S., Gupta, A., & Pathak, D. (2022) · Robotics: Science and Systems · doi:10.15607/rss.2022.xviii.026 · Cited by 86 · see citing works

Dynamic Movement Primitives Based Robot Skills Learning

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Demonstration-Guided Motion Planning

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Impedance Control Architecture for Robotic-Assisted Mold Polishing Based on Human Demonstration

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Dynamic Movement Primitives: Volumetric Obstacle Avoidance Using Dynamic Potential Functions

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Concept2Robot: Learning manipulation concepts from instructions and human demonstrations

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Task-Based Robot Grasp Planning Using Probabilistic Inference

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RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot

Fang, H.-S., Fang, H., Tang, Z., Liu, J., Wang, C., Wang, J., Zhu, H., & Lu, C. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611615 · Cited by 84 · see citing works

BM: An iterative algorithm to learn stable non-linear dynamical systems with Gaussian mixture models

Khansari-Zadeh, S. M., & Billard, A. (2010) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2010.5510001 · Cited by 76 · see citing works

Learning task-parameterized dynamic movement primitives using mixture of GMMs

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Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

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Imitation learning of globally stable non-linear point-to-point robot motions using nonlinear programming

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Fast and Stable Learning of Dynamical Systems Based on Extreme Learning Machine

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A system for learning continuous human-robot interactions from human-human demonstrations

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Transition State Clustering: Unsupervised Surgical Trajectory Segmentation for Robot Learning

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Interactive imitation learning of object movement skills

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From dynamic movement primitives to associative skill memories

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Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning.

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TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning

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Overcoming some drawbacks of Dynamic Movement Primitives

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Learning symbolic representations of actions from human demonstrations

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Toward Orientation Learning and Adaptation in Cartesian Space

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SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards

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To imitate or not to imitate: Boosting reinforcement learning-based construction robotic control for long-horizon tasks using virtual demonstrations

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Towards grounding concepts for transfer in goal learning from demonstration

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