On the Implementation of Behavior Trees in Robotics

There is a growing interest in Behavior Trees (BTs) as a tool to describe and implement robot behaviors. BTs were devised in the video game industry and their adoption in robotics resulted in the development of ad-hoc libraries to design and execute BTs that fit complex robotics software architectures. While there is broad consensus on how BTs work, some characteristics rely on the implementation choices done in the specific software library used. In this letter, we outline practical aspects in the adoption of BTs and the solutions devised by the robotics community to fully exploit the advantages of BTs in real robots. We also overview the solutions proposed in open-source libraries used in robotics, we show how BTs fit in robotic software architecture, and we present a use case example

Behavior trees as a control architecture in the automatic modular design of robot swarms

Previous research has shown that automatically combining low-level behaviors into a probabilistic finite state machine produces control software that crosses the reality gap satisfactorily. In this paper, we explore the possibility of adopting behavior trees as an architecture for the control software of robot swarms. We introduce Maple: an automatic design method that combines preexisting modules into behavior trees. To highlight the potential of this control architecture, we present robot experiments in which we compare Maple with Chocolate and EvoStick on two missions: foraging and aggregation. Chocolate and EvoStick are two previously published automatic design methods. Chocolate is a modular method that generates probabilistic finite state machines and EvoStick is a traditional evolutionary robotics method. The results of the experiments indicate that behavior trees are a viable and promising architecture to automatically generate control software for robot swarms.info:eu-repo/semantics/publishe