Task and Motion Planning for Multi-Agent Systems

In dynamic environments, where the number and location of tasks are unknown to agents, robots need to explore the environment to find tasks before accomplishing them. In most real-world problems, robots need to be sufficiently dexterous, which inevitably makes robots relatively heavy and incapable of agile exploration. In this project, we aim to address this problem by considering each task composed of sequential subtasks, each possible to be done only by a certain type of agent. We Introduced the notion of hunter-and-gatherer approach to address different aspects of the problem such as multi-agent task allocation, exploration, and coordination.