Multiagent adjustable autonomy framework (MAAF) for multirobot, multihuman teams

Citation:

A. Freedy, O. Sert, E. Freedy, G. Weltman, J. Mcdonough, Milind Tambe, and Tapana Gupta. 2008. “Multiagent adjustable autonomy framework (MAAF) for multirobot, multihuman teams .” In International symposium on collaborative technologies (CTS).

Abstract:

This paper describes the ongoing development of a Multiagent Adjustable Autonomy Framework (MAAF) for multi-robot, multi-human teams performing tactical maneuvers. The challenge being addressed in this SBIR Phase I R&D project is how to exploit fully the unique capabilities of heterogeneous teams composed of a mixture of Robots, Agents or Persons (RAPs): that is, how to improve the safety, efficiency, reliability and cost of achieving mission goals while maintaining dynamic adaptation to the unique limitations and contingencies of a real-world operating environment. Our response to this challenge is the creation of a new infrastructure that will facilitate cooperative and collaborative performance of human and robots as equal team partners through the application of advances in goal-oriented, multiagent planning and coordination technology. At the heart of our approach is the USC Teamcore Group’s Machinetta, a state-of-the-art robot proxy framework with adjustable autonomy. Machinetta facilitates robot-human role allocation decisions and collaborative sharing of team tasks in the non-deterministic and unpredictable military environment through the use of a domain-independent teamwork model that supports flexible teamwork. This paper presents our innovative proxy architecture and its constituent algorithms, and also describes our initial demonstration of technical feasibility in a realistic simulation scenario.
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