A Distributed Control Architecture for Collaborative Multi-Robot Task Allocation
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This thesis addresses the problem of task allocation for multi-robot systems that perform tasks with complex, hierarchical representations which contain different types of ordering constraints and multiple paths of execution. We propose a distributed multi-robot control architecture that addresses the above challenges and makes the following contributions: i) it allows for online, dynamic allocation of robots to various steps of the task, ii) it ensures that the collaborative robot system will obey all of the task constraints and iii) it allows for opportunistic, flexible task execution given different environmental conditions. This architecture uses a distributed messaging system to allow the robots to communicate. Each robot uses its own state and team member states to keep track of the progress on a given task and identify which sub-tasks to perform next using an activation spreading mechanism. We demonstrate the proposed architecture on a team of two humanoid robots (a Baxter and a PR2) performing hierarchical tasks.