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
Socially guided machine learning
Socially guided machine learning
Confidence-based policy learning from demonstration using Gaussian mixture models
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Learning about objects with human teachers
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
A survey of robot learning from demonstration
Robotics and Autonomous Systems
Learning multirobot joint action plans from simultaneous task execution demonstrations
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction
Learning collaborative team behavior from observation
Expert Systems with Applications: An International Journal
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Solutions to complex tasks often require the cooperation of multiple robots, however, developing multi-robot policies can present many challenges. In this work, we introduce teaching by demonstration in the context of multi-robot tasks, enabling a single teacher to instruct multiple robots to work together through a demonstration of the desired behavior. Within this framework, we contribute two approaches for teaching coordination based on different communication and information sharing strategies. To enable the teacher to divide attention between multiple robots, each robot uses a confidence-based algorithm that allows it to regulate its autonomy and determine the need for demonstration. Evaluation is performed using two Sony QRIO robots learning a real-world collaborative ball sorting task.