On Robotic Assembly and Optimization-Based Control of Industrial Manipulators

Robotic manipulators are essential tools of industry. They are ubiquituous in modern factories, and they are starting to become more commonplace everywhere else. The trend in robotic manipulators is to move towards allowing for more human-robot collaboration, to allow for sensor-based tasks, and to perform classical industrial tasks such as assembly in new and unforeseen environments. These trends enable small and medium businesses to lower the cost of automation by simplifying robot programming. The core interest of this thesis is an idealized automatic assembly system, capable of generating and executing robot programs based on CAD models. Such a system is challenging to realize, as it is composed of many subcomponents that are large research topics in and of themselves. From the control-theoretic perspective, much of the work lies in task specification and relating assembly of the parts to robot motions, as is the core discussion in one of the papers. The papers present control strategies intended for on-line control of an industrial manipulator. As optimization techniques may have slow execution time, the timings of the different control strategies are a recurring topic in the papers. The communication and tracking latency of a KUKA robot system is also investigated when developing an open-source control interface to the KUKA system. This thesis presents contributions in robotic assembly and optimization based control of industrial manipulators. The papers in this thesis aim to address some shortcomings in the robotics literature that were found when investigating the idealized system. The accompanying text gives a brief introduction to the history of robotics, as well as an overview of some of the robotics literature