Behavior Trees

First book on Behavior Trees.

The book, titled Behavior Trees in Robotics and AI: An Introduction, is published by CRC Press Taylor & Francis. You can buy the hardcover copy and the ebook either on the CRC Press Store or Amazon.

Please make sure the pages are printed in color (see details here).

The free pre-print is available here.

Behavior Trees in Formal Verification

We are introducing Behavior Trees in the RobMoSys framework and we are working towards the development of formal verification tools to assess the correctness of defined behaviors in the form of Behavior Trees.

Blended Acting and Planning using Behavior Trees

We proposed a framework that automatically synthesizes a Behavior Tree that satisfies a given goal. It is an attempt to address the challenges regarding blending planning and acting: hierarchically organized deliberation and continual planning and deliberation.

Reinforcement Learning Using Behavior Trees

Taking advantage of modularity and reactiveness of Behavior Trees, we propose a model-free Automated Planned framework using Genetic Programming to derive an action plan for an autonomous agent to achieve a given goal in unknown environments. The advantages of the proposed approach are based on the advantages of BT over a common FSM. 

Stochastic Behavior Trees

Stochastic Behavior Trees are an extension of Behavior Trees presented at ICRA 2014 where each leaf node is described by its success/failure probabilities and execution times. The recursive structure of the tree then enables us to step by step propagate such probabilities and time from the leaves to the root.

Structural Properties of Behavior Trees

Using standard tools of robot control theory, it is possible to evaluate structural properties such as robustness and safety of an action plan described by a Behavior Tree. In IROS 2014 we presented how to build action plans that are safe and robust.