A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advanced Robotics: Redundancy and Optimization
Advanced Robotics: Redundancy and Optimization
Natural methods for robot task learning: instructive demonstrations, generalization and practice
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
2006 Special Issue: Modeling attention to salient proto-objects
Neural Networks
Learning and generalization of motor skills by learning from demonstration
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Task-level imitation learning using variance-based movement optimization
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Imitation learning with generalized task descriptions
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Markerless human motion tracking with a flexible model and appearance learning
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Learning motor primitives for robotics
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Automatic selection of task spaces for imitation learning
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fast detection of arbitrary planar surfaces from unreliable 3D data
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Robot Programming by Demonstration
Robot Programming by Demonstration
Towards performing everyday manipulation activities
Robotics and Autonomous Systems
Visual learning by imitation with motor representations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On Learning, Representing, and Generalizing a Task in a Humanoid Robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interaction learning for dynamic movement primitives used in cooperative robotic tasks
Robotics and Autonomous Systems
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In this paper we present a new robot control and learning system that allows a humanoid robot to extend its movement repertoire by learning from a human tutor. The focus is learning and imitating motor skills to move and position objects. We concentrate on two major aspects. First, the presented teaching and imitation scenario is fully interactive. A human tutor can teach the robot which is in turn able to integrate newly learned skills into different movement sequences online. Second, we combine a number of novel concepts to enhance the flexibility and generalization capabilities of the system. Generalization to new tasks is obtained by decoupling the learned movements from the robot's embodiment using a task space representation. It is chosen automatically from a commonly used task space pool. The movement descriptions are further decoupled from specific object instances by formulating them with respect to so-called linked objects. They act as references and can interactively be bound to real objects. When executing a learned task, a flexible kinematic description allows to change the robot's body schema online and thereby apply the learned movement relative to different body parts or new objects. An efficient optimization scheme adapts movements to such situations performing online obstacle and self-collision avoidance. Finally, all described processes are combined within a comprehensive architecture. To demonstrate the generalization capabilities we show experiments where the robot performs a movement bimanually in different environments, although the task was demonstrated by the tutor only one-handed.