Teaching multi-robot coordination using demonstration of communication and state sharing

ABSTRACT

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.

REFERENCES

• 1: Sonia Chernova , Manuela Veloso, Confidence-based policy learning from demonstration using Gaussian mixture models, Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, May 14-18, 2007, Honolulu, Hawaii [doi>10.1145/1329125.1329407]
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• 4: Monica N. Nicolescu , Maja J. Mataric, Natural methods for robot task learning: instructive demonstrations, generalization and practice, Proceedings of the second international joint conference on Autonomous agents and multiagent systems, July 14-18, 2003, Melbourne, Australia [doi>10.1145/860575.860614]
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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.9 Robotics

General Terms:
Algorithms, Performance

Keywords:
learning from demonstration