Behavior Trees in Robotics and AI: An Introduction

A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game. BTs are a very efficient way of creating complex systems that are both modular and reactive. These properties are crucial in many applications, which has led to the spread of BT from computer game programming to many branches of AI and Robotics. In this book, we will first give an introduction to BTs, then we describe how BTs relate to, and in many cases generalize, earlier switching structures. These ideas are then used as a foundation for a set of efficient and easy to use design principles. Properties such as safety, robustness, and efficiency are important for an autonomous system, and we describe a set of tools for formally analyzing these using a state space description of BTs. With the new analysis tools, we can formalize the descriptions of how BTs generalize earlier approaches. We also show the use of BTs in automated planning and machine learning. Finally, we describe an extended set of tools to capture the behavior of Stochastic BTs, where the outcomes of actions are described by probabilities. These tools enable the computation of both success probabilities and time to completion

A layered control architecture for mobile robot navigation

A Thesis submitted to the University Research Degree Committee in fulfillment ofthe requirements for the degree of DOCTOR OF PHILOSOPHY in RoboticsThis thesis addresses the problem of how to control an autonomous mobile robot navigation in indoor environments, in the face of sensor noise, imprecise information, uncertainty and limited response time. The thesis argues that the effective control of autonomous mobile robots can be achieved by organising low level and higher level control activities into a layered architecture. The low level reactive control allows the robot to respond to contingencies quickly. The higher level control allows the robot to make longer term decisions and arranges appropriate sequences for a task execution. The thesis describes the design and implementation of a two layer control architecture, a task template based sequencing layer and a fuzzy behaviour based low level control layer. The sequencing layer works at the pace of the higher level of abstraction, interprets a task plan, mediates and monitors the controlling activities. While the low level performs fast computation in response to dynamic changes in the real world and carries out robust control under uncertainty. The organisation and fusion of fuzzy behaviours are described extensively for the construction of a low level control system. A learning methodology is also developed to systematically learn fuzzy behaviours and the behaviour selection network and therefore solve the difficulties in configuring the low level control layer. A two layer control system has been implemented and used to control a simulated mobile robot performing two tasks in simulated indoor environments. The effectiveness of the layered control and learning methodology is demonstrated through the traces of controlling activities at the two different levels. The results also show a general design methodology that the high level should be used to guide the robot's actions while the low level takes care of detailed control in the face of sensor noise and environment uncertainty in real time

Desarrollo automatizado de sistemas teleo-reactivos a partir de objetivos: un enfoque basado en componentes y dirigido por modelos

[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. Está formada por un total de cuatro artículos publicados en revistas del segundo cuartil del Journal Citation Reports. El artículo “A systematic literature review of the Teleo-Reactive paradigm” ofrece una completa revisión sistemática de la literatura existente sobre el paradigma Teleo-Reactivo desde su presentación por el profesor Nils Nilsson en el año 1994. Su papel en esta tesis es el de servir de estado del arte de dicho paradigma, ofreciendo una buena perspectiva de la evolución de los sistemas Teleo-Reactivos desde su formulación hasta el presente. Para poder desarrollar sistemas Teleo-Reactivos a partir de objetivos, surgió la necesidad de especificar los requisitos de estos sistemas usando el lenguaje más apropiado. Ese es uno de los objetivos principales del artículo “A controlled experiment to evaluate the understandability of KAOS and i* for modeling Teleo-Reactive systems”. Como resultado de dicho trabajo se decidió utilizar i* dado que el experimento realizado mostró que las especificaciones realizadas con dicho lenguaje resultaban ligeramente más comprensibles que las realizadas con KAOS. Aunque i* resultaba más comprensible a la hora de especificar requisitos para sistemas Teleo-Reactivos, también presentaba ciertas debilidades. Estas debilidades han sido descritas detalladamente en el artículo “A family of experiments to evaluate the understandability of TRiStar and i* for modeling Teleo-Reactive systems”, en el que además se propone una extensión al lenguaje que permite superarlas. La extensión propuesta se denomina TRiStar y fue inicialmente presentada en [Morales15]. TRiStar ha demostrado superar los problemas de comprensibilidad identificados en i* en el modelado de sistemas Teleo-Reactivos mediante una familia de experimentos realizada con estudiantes de últimos cursos de grado y con desarrolladores software experimentados, cuyos resultados se exponen exhaustivamente en el artículo mencionado. En él se describe, además, un mecanismo que permite obtener mediante transformación de modelos el programa Teleo-Reactivo equivalente a un diagrama TRiStar dado. TRiStar permite, por lo tanto, partiendo de los objetivos de un sistema Teleo-Reactivo obtener un diagrama que especifique su comportamiento. Ese diagrama puede ser transformado en un programa Teleo-Reactivo equivalente. Y siguiendo las transformaciones descritas en “From Teleo-Reactive specifications to architectural components: a model-driven approach” se puede obtener a partir del programa Teleo-Reactivo el modelo de componentes y la máquina de estados que describe el comportamiento de cada uno de esos componentes. Con estos elementos y usando un framework como el descrito en [Iborra09] se cerraría el proceso de desarrollo del sistema Teleo-Reactivo. Como resultado de las investigaciones realizadas en el transcurso de esta tesis, y aunque no forma parte del compendio, hay un quinto artículo [Sánchez16] que está en segunda revisión en el Journal of Systems and Software en el que se estudian las posibilidades de introducir requisitos de tiempo real cuando se sigue el enfoque Teleo-Reactivo desde el modelado a la implementación de un sistema. Tras realizar un estudio del tipo de restricciones temporales que se pueden imponer desde el punto de vista Teleo-Reactivo, se considera la posibilidad de utilizar TeleoR [Clark14] para incorporar dichas restricciones y se proponene una serie de extensiones a TRiStar para permitir representar requisitos temporales. Estas extensiones dan lugar a lo que hemos llamado TRiStar+. [ENG] This doctoral dissertation has been presented in the form of thesis by publication. It is comprised of four articles indexed in the second quartile of the Journal Citation Reports. The article “A systematic literature review of the Teleo-Reactive paradigm” offers a complete systematic review of the existing literature on the Teleo-Reactive paradigm since Prof. Nils Nilsson presented it in 1994. It plays the role of state of the art of that paradigm, showing a perspective of the evolution of Teleo-Reactive systems from their formulation to present time. In order to develop Teleo-Reactive systems starting from its goals, there is the need of specifying the requirements of these systems using the most adequate language. That is one of the main objectives of the article “A controlled experiment to evaluate the understandability of KAOS and i* for modeling Teleo-Reactive systems”. As a result, we decided to use i* because the experiment showed that i* specifications where slightly more understandable than those made using KAOS. Although i* was more understandable when specifying requirements for Teleo-Reactive systems, the experiment also showed some shortcomings. These shortcomings have been deeply described in the article “A family of experiments to evaluate the understandability of TRiStar and i* for modeling Teleo-Reactive systems”. In this article, an extension to i* is proposed in order to overcome the identified limitations. The proposed extension is named TRiStar and was initially presented at [Morales15]. TRiStar has shown to be more understandable than i* when modeling Teleo-Reactive systems through a family of experiments done with last year students and experienced software developers, whose results are described in the aforementioned article. In that article, a mechanism to obtain a Teleo-Reactive program starting from a TRiStar diagram is also described. Therefore, TRiStar allows obtaining a diagram which specifies the behavior of a Teleo-Reactive system starting from its goals. That diagram can be transformed into an equivalent Teleo-Reactive program. Then, following the transformations described in “From Teleo-Reactive specifications to architectural components: a model-driven approach”, a component model and the state machine describing the behavior of each of those components can be obtained. With these elements and using a framework as that described in [Iborra09], the development process of the Teleo-Reactive system would be finished. As a result of the research carried out during this dissertation there is another article, which is not comprised in the compilation, in second revision at the Journal of Systems and Software [Sánchez16]. In that article, after making a study of the type of timing constraints from the TR perspective, we consider the possibility of using TeleoR [Clark14] for incorporating such constraints. Some extensions on TRiStar notation are proposed to represent temporal requirements. Those extensions have been named TRiStar+.[ENG] This doctoral dissertation has been presented in the form of thesis by publication. It is comprised of four articles indexed in the second quartile of the Journal Citation Reports. The article “A systematic literature review of the Teleo-Reactive paradigm” offers a complete systematic review of the existing literature on the Teleo-Reactive paradigm since Prof. Nils Nilsson presented it in 1994. It plays the role of state of the art of that paradigm, showing a perspective of the evolution of Teleo-Reactive systems from their formulation to present time. In order to develop Teleo-Reactive systems starting from its goals, there is the need of specifying the requirements of these systems using the most adequate language. That is one of the main objectives of the article “A controlled experiment to evaluate the understandability of KAOS and i* for modeling Teleo-Reactive systems”. As a result, we decided to use i* because the experiment showed that i* specifications where slightly more understandable than those made using KAOS. Although i* was more understandable when specifying requirements for Teleo-Reactive systems, the experiment also showed some shortcomings. These shortcomings have been deeply described in the article “A family of experiments to evaluate the understandability of TRiStar and i* for modeling Teleo-Reactive systems”. In this article, an extension to i* is proposed in order to overcome the identified limitations. The proposed extension is named TRiStar and was initially presented at [Morales15]. TRiStar has shown to be more understandable than i* when modeling Teleo-Reactive systems through a family of experiments done with last year students and experienced software developers, whose results are described in the aforementioned article. In that article, a mechanism to obtain a Teleo-Reactive program starting from a TRiStar diagram is also described. Therefore, TRiStar allows obtaining a diagram which specifies the behavior of a Teleo-Reactive system starting from its goals. That diagram can be transformed into an equivalent Teleo-Reactive program. Then, following the transformations described in “From Teleo-Reactive specifications to architectural components: a model-driven approach”, a component model and the state machine describing the behavior of each of those components can be obtained. With these elements and using a framework as that described in [Iborra09], the development process of the Teleo-Reactive system would be finished. As a result of the research carried out during this dissertation there is another article, which is not comprised in the compilation, in second revision at the Journal of Systems and Software [Sánchez16]. In that article, after making a study of the type of timing constraints from the TR perspective, we consider the possibility of using TeleoR [Clark14] for incorporating such constraints. Some extensions on TRiStar notation are proposed to represent temporal requirements. Those extensions have been named TRiStar+.Universidad Politécnica de CartagenaPrograma Oficial de Doctorado en Tecnologías de la Información y Comunicacione

Reasoning about real-time teleo-reactive programs

The teleo-reactive programming model is a high-level approach to implementing real-time control programs that react dynamically to changes in their environment. Teleo-reactive programs are particularly useful for implementing controllers in autonomous agents. In this paper we present formal techniques for reasoning about robust teleo-reactive programs.We develop a temporal logic over continuous intervals, which we use to formalise the semantics of teleo-reactive programs. To facilitate compositional reasoning about a program and its environment, we use rely/guarantee style specications. We also present several theorems for simplifying proofs of teleo-reactive programs that control goal-directed agents

Improving the Parallel Execution of Behavior Trees

Behavior Trees (BTs) have become a popular framework for designing controllers of autonomous agents in the computer game and in the robotics industry. One of the key advantages of BTs lies in their modularity, where independent modules can be composed to create more complex ones. In the classical formulation of BTs, modules can be composed using one of the three operators: Sequence, Fallback, and Parallel. The Parallel operator is rarely used despite its strong potential against other control architectures as Finite State Machines. This is due to the fact that concurrent actions may lead to unexpected problems similar to the ones experienced in concurrent programming. In this paper, we introduce Concurrent BTs (CBTs) as a generalization of BTs in which we introduce the notions of progress and resource usage. We show how CBTs allow safe concurrent executions of actions and we analyze the approach from a mathematical standpoint. To illustrate the use of CBTs, we provide a set of use cases in robotics scenarios