An Extended Convergence Result for Behaviour Tree Controllers
This work addresses convergence issues for behavior trees, a modular control framework widely used in robotics, but it appears incremental as it builds on prior results.
The paper tackles the problem of proving convergence for behavior tree controllers in robotics, generalizing earlier results to include new cases of cyclic switching and broader families of BTs.
Behavior trees (BTs) are an optimally modular framework to assemble hierarchical hybrid control policies from a set of low-level control policies using a tree structure. Many robotic tasks are naturally decomposed into a hierarchy of control tasks, and modularity is a well-known tool for handling complexity, therefor behavior trees have garnered widespread usage in the robotics community. In this paper, we study the convergence of BTs, in the sense of reaching a desired part of the state space. Earlier results on BT convergence were often tailored to specific families of BTs, created using different design principles. The results of this paper generalize the earlier results and also include new cases of cyclic switching not covered in the literature.