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Using Behavior Trees for Coordination of Skills in Modular Reconfigurable CPPMs

Aleksandr Sidorenko; Jesko Hermann; Martin Ruskowski
In: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Pages 1-8, IEEE, 2022.


A skill-based engineering approach uses the concept of skill to abstract machine-specific functionality with a generic interface and common behavior. A skill is treated as a “control level service” and is used to build service-oriented architectures. Though the question of robust and flexible coordination of skills is still open. Current approaches to skills’ composition result in tightly-coupled control structures. To allow frequent and rapid system’s reconfiguration a framework to flexibly build complex behaviors from reusable components is needed. Behavior Trees (BTs) have proven to be a powerful tool for specifying characters’ behaviors in the gaming industry and recently is getting a lot of attention in the robotics community as well as academia. An approach of using BTs for coordination of industrial skills is proposed in this paper. Combining behavior trees with the existing skill models enhances separation of concerns and modularity of control systems in the factory automation domain. Firstly, we define the requirements for a skills coordination layer and discuss some key properties of BTs that allow to satisfy these requirements. Secondly, we introduce a skill model, which utilizes BTs and has several advantages over the current skill models. Thirdly, we introduce a concept of distributed BTs to effectively distribute functionality over different computational platforms. Finally, we present a small proof of concept example to test feasibility of the proposed approach.