Traderbots: a new paradigm for robust and efficient multirobot coordination in dynamic environments

The challenge of efficient multirobot coordination has risen to the forefront of robotics research in recent years. The wide range of applications demanding multirobot solutions motivates interest in this problem. In general, multirobot coordination strategies assume either a centralized approach, where a single agent plans for the group, or a distributed approach, where each robot is responsible for its own planning. Inherent to many centralized approaches are difficulties such as intractable solutions for large groups, sluggish response to changes in the local environment, heavy communication requirements, and brittle systems with single points of failure. The key advantage of centralized approaches is that they can produce globally optimal plans. While most distributed approaches can overcome these difficulties, they can only produce suboptimal plans because they cannot take full advantage of information available to all team members. This work develops TraderBots, a market-based coordination approach that is inherently distributed, but can also opportunistically form centralized subgroups to improve efficiency. Robots are self-interested with the primary goal of maximizing individual profits. The revenue and cost models and the rules of engagement are designed so that maximizing individual profit has the benevolent effect of, on average, moving the team toward the globally optimal solution. This approach inherits the flexibility of markets in allowing cooperation and competition to emerge opportunistically. This dissertation addresses the multirobot coordination problem for autonomous robotic teams executing tasks in dynamic environments where it is efficient solutions are desirable. Contributions of this dissertation are the first extensive investigation of the application of market-based techniques to multirobot coordination, the most versatile coordination-approach for dynamic multirobot application domains, the first market-based approach to multirobot coordination that allows opportunistic optimization by “leaders”, the first in-depth investigation of the requirements for robust multirobot coordination in dynamic environments, the most extensive implementation of a market-based approach to multirobot coordination, and first steps in a systematic approach for evaluating and comparing multirobot coordination strategies.