Imitation learning: A survey of learning methods

A Hussein, MM Gaber, E Elyan, C Jayne - ACM Computing Surveys …, 2017 - dl.acm.org
Imitation learning techniques aim to mimic human behavior in a given task. An agent (a
learning machine) is trained to perform a task from demonstrations by learning a map** …

Dynamic movement primitives in robotics: A tutorial survey

M Saveriano, FJ Abu-Dakka… - … Journal of Robotics …, 2023 - journals.sagepub.com
Biological systems, including human beings, have the innate ability to perform complex
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …

Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning

S Krishnan, A Garg, S Patil, C Lea… - … journal of robotics …, 2017 - journals.sagepub.com
Demonstration trajectories collected from a supervisor in teleoperation are widely used for
robot learning, and temporally segmenting the trajectories into shorter, less-variable …

[HTML][HTML] Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization

L Roveda, M Magni, M Cantoni, D Piga… - Robotics and Autonomous …, 2021 - Elsevier
Robots are increasingly exploited in production plants. Within the Industry 4.0 paradigm, the
robot complements the human's capabilities, learning new tasks and adapting itself to …

Robotics and neuroscience

D Floreano, AJ Ijspeert, S Schaal - Current Biology, 2014 - cell.com
In the attempt to build adaptive and intelligent machines, roboticists have looked at
neuroscience for more than half a century as a source of inspiration for perception and …

An autonomous manipulation system based on force control and optimization

L Righetti, M Kalakrishnan, P Pastor, J Binney… - Autonomous …, 2014 - Springer
In this paper we present an architecture for autonomous manipulation. Our approach is
based on the belief that contact interactions during manipulation should be exploited to …

Neuro-musculoskeletal modeling reveals muscle-level neural dynamics of adaptive learning in sensorimotor cortex

T DeWolf, S Schneider, P Soubiran, A Roggenbach… - bioRxiv, 2024 - biorxiv.org
The neural activity of the brain is intimately coupled to the dynamics of the body. Yet how our
hierarchical sensorimotor system dynamically orchestrates the generation of movement …

Learning coupling terms for obstacle avoidance

A Rai, F Meier, A Ijspeert… - 2014 IEEE-RAS …, 2014 - ieeexplore.ieee.org
Autonomous manipulation in dynamic environments is important for robots to perform
everyday tasks. For this, a manipulator should be capable of interpreting the environment …

Robot control based on motor primitives: A comparison of two approaches

MC Nah, J Lachner, N Hogan - The International Journal of …, 2024 - journals.sagepub.com
Motor primitives are fundamental building blocks of a controller which enable dynamic robot
behavior with minimal high-level intervention. By treating motor primitives as basic …

A fast transfer reinforcement learning model for transferring force-based human speed adjustment skills to robots for collaborative assembly posture alignment

H Sun, T Zhang, J Han, H Chu - Advanced Engineering Informatics, 2024 - Elsevier
Human-robot collaboration demonstrates significant autonomy and flexibility, making it
highly suitable for personalized and adaptable production tasks. However, the disparity …