Intelligent Coordination for Multi-Agent Systems

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In many real-world autonomous systems, teams of agents have to assign tasks among themselves and then plan trajectories to visit the task locations. The agents may have to avoid proximity to humans and each other in congested and dynamic environments or compete for resources, yet working cooperatively toward a common objective. Applications of such multi-agent systems include autonomous aircraft towing vehicles, automated warehouse robots, automated-guided port vehicles, game characters in video games, patrolling robots, search-and-rescue robots, indoor service robots, swarms of unmanned ground and aerial vehicles, and other multi-robot systems. The coordination of autonomous operations is a fundamental building block for these multi-agent systems but often becomes computationally challenging as the number of agents and the operating time of agents increase. This research program thus aims to establish algorithmic foundations for making efficient, effective, and robust decisions to coordinate autonomous operations for these multi-agent systems. This research program will study different task and motion coordination problems, their complexities, algorithms for solving them, and their applications. It will also demonstrate how our techniques can benefit real-world applications of multi-agent systems using both standard robot simulators and teams of ground and aerial robots. Specifically, this research program will involve (1) developing theoretical insights that characterize the computational complexity and capture the combinatorial structure of novel formulations of multi-agent coordination problems, (2) providing efficient and effective algorithmic solutions to these problems by exploiting their combinatorial structure, and (3) designing strategies that refine these solutions into executable plans for real robots even in the presence of humans, system dynamics, or uncertainties. Teams of intelligent agents, including millions of self-driving cars, autonomous drones, and service robots, will soon become an intrinsic part of our daily life. We believe that our techniques will have a significant impact on coordinating and regulating these agents and making them smarter to better collaborate with and assist humans. This research program will build expertise in the interdisciplinary area of artificial intelligence and robotics within Canada. It will also benefit Canadian government agencies that aim to regulate ground and aerial traffic of these agents and enhance the competitiveness of Canadian technology companies that build and use teams of intelligent agents. The algorithmic techniques will shorten the operating time of these agents and reduce the number of agents needed, while keeping the same throughput of the system, thus resulting in a positive environmental impact on pollution, energy consumption, land usage, and congestion.