Author:
Nidhi Kalra
Robotics Institute
Carnegie Mellon University
Abstract:
This thesis explores the coordination challenges posed by real-world multirobot domains that require planned tight coordination between teammates throughout execution. These domains involve solving a multi-agent planning problem in which the actions of robots are tightly coupled. Because of uncertainty in the environment and the team, they also require persistent tight coordination between teammates throughout execution.
This thesis proposes an approach to these problems in which the complexity and strength of the coordination adapt to the difficulty of the problem. Our approach, called Hoplites, is a market-based framework that selectively injects pockets of complex coordination into a primarily distributed system by enabling robots to purchasing each other's participation in tightly-coupled plans over the market. We discuss how it is widely applicable to real-world problems because it is general, computationally feasible, scalable, operates under uncertainty, and improves solutions with new information. Experiments show that our approach significantly outperforms existing coordination methods.
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