Integrated task and motion scheduling for flexible manufacturing

This thesis considers the problem of coordinating multiple industrial manipulators with overlapping workspaces working on a shared set of tasks. The work is motivated by the vast amount of manual manufacturing tasks we could automate. However, these tasks are often not worth automating because the batch size is too small, and today's automation methods require too much engineering effort. A large part of the engineering effort goes into manually optimizing schedules, i.e., deciding which robot does what and when.
The main research question regards how to increase the operation efficiency of closely interacting multi-robot systems in changing tasks. This question is divided into three subquestions addressing (i) the formulation and optimization of the automation task, (ii) how humans can efficiently interact with such an optimization framework, and (iii) how to deploy the solution schedules on a robotic system safely.
This work develops automatic planning and scheduling techniques for the identified problem class to answer these questions. It embeds them into a system featuring a multi-modal user interface and a safe execution engine.