Preparation and control of intelligent automation systems

Sammanfattning: In the automation systems of tomorrow, it is likely that the devices included have various degrees of autonomy, and include advanced algorithms for perception and control. Human operators will be expected to work together with collaborative robots as well as with roaming robots for material handling. The volatile nature of the environment of such intelligent automation systems lead to an enormous amount of possible situations that can arise and which need to be suitably handled. This complexity makes development of control systems for intelligent automation systems difficult using traditional methods. As an alternative, this thesis presents a model-based control framework, which uses a combination of formal specification and automated planning. The proposed framework allows for defining the intentions of the automation system on a high level, which enables decisions that influence when things should occur to be modeled using logical constraints, rather than programming. To achieve a modular framework, low level, reusable, resource models are composed by 1) formal specification to ensure safety and 2) applying an abstraction called an operation, which couples the reusable resources to the intentions of the system. By planning also the resources' detailed actions, the operations can, when possible, be completed regardless of the resources' current state. This eases error-recovery, as resources do not have to be reset when an error occurs. Additionally, the thesis proposes an iterative and interactive workflow for integrating the proposed model-based control framework into a virtual preparation process, using computer-based simulation as a tool for validating formal specifications. The control framework allows for adding new constraints to a running system, enabling an efficient and interactive preparation process. The framework has been applied to a use case from final assembly, which features human-robot collaboration. Experimental results on the ability to handle unforeseen errors and planning performance are presented.