Software Engineering and Swarm-Based Systems

We discuss two software engineering aspects in the development of complex swarm-based systems. NASA researchers have been investigating various possible concept missions that would greatly advance future space exploration capabilities. The concept mission that we have focused on exploits the principles of autonomic computing as well as being based on the use of intelligent swarms, whereby a (potentially large) number of similar spacecraft collaborate to achieve mission goals. The intent is that such systems not only can be sent to explore remote and harsh environments but also are endowed with greater degrees of protection and longevity to achieve mission goals

Requirements of an Integrated Formal Method for Intelligent Swarms

NASA is investigating new paradigms for future space exploration, heavily focused on the (still) emerging technologies of autonomous and autonomic systems [47, 48, 49]. Missions that rely on multiple, smaller, collaborating spacecraft, analogous to swarms in nature, are being investigated to supplement and complement traditional missions that rely on one large spacecraft [16]. The small spacecraft in such missions would each be able to operate on their own to accomplish a part of a mission, but would need to interact and exchange information with the other spacecraft to successfully execute the mission

Autonomous and Autonomic Swarms

A watershed in systems engineering is represented by the advent of swarm-based systems that accomplish missions through cooperative action by a (large) group of autonomous individuals each having simple capabilities and no global knowledge of the group s objective. Such systems, with individuals capable of surviving in hostile environments, pose unprecedented challenges to system developers. Design and testing and verification at much higher levels will be required, together with the corresponding tools, to bring such systems to fruition. Concepts for possible future NASA space exploration missions include autonomous, autonomic swarms. Engineering swarm-based missions begins with understanding autonomy and autonomicity and how to design, test, and verify systems that have those properties and, simultaneously, the capability to accomplish prescribed mission goals. Formal methods-based technologies, both projected and in development, are described in terms of their potential utility to swarm-based system developers

Experiences applying Formal Approaches in the Development of Swarm-Based Space Exploration Systems

NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nan0 Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Sustainable and Autonomic Space Exploration Missions

Visions for future space exploration have long term science missions in sight, resulting in the need for sustainable missions. Survivability is a critical property of sustainable systems and may be addressed through autonomicity, an emerging paradigm for self-management of future computer-based systems based on inspiration from the human autonomic nervous system. This paper examines some of the ongoing research efforts to realize these survivable systems visions, with specific emphasis on developments in Autonomic Policies

Top-Down & Bottom-Up Approaches to Robot Design

This thesis presents a study of different engineering design methodologies and demonstrates their effectiveness and limitations in actual robot designs. Some of these methods were blended together with focus on providing an easily interpreted project design flow while implementing more bottom-up, or feedback, elements into the design methodology. Typically design methods are learned through experience, and design taught in academia aims to shape and formalize previous experience. Usually, inexperienced engineers are taught approaches resembling the Verein Deutscher Ingenieure (VDI) 2221 process. This method presented by the Association of German Engineers in 2006 is regarded as the general system design process. This introductory process is largely left open to interpretation, and it is often unclear when to implement feedback in the design process. The objective of this thesis is to investigate the roles of top-down and bottom-up processes, and how to integrate them in the robot design methodology. The proposed approach utilizes several components from existing design methods. There are three main conditional loops within the proposed approach. The first loop focuses on defining the problem in a top-down manner through logical decomposition, defining technical requirements, researching solutions, and conducting a trade study. These four steps are done iteratively until reaching the bottom of the system, the most primitive components. This is followed by a modeling and analysis loop. This works from the bottom to the top of the design in preparation for manufacturing and validation. The final loop of the proposed approach focuses on validation and verification. The testing and manufacturing involved allows for alterations to the design to fulfill the original technical requirements. These three loops occur until a proof of concept is achieved. The proposed method is intended to be applied iteratively. The first pass of the method results in a proof of concept, while the second results in a preproduction prototype, and the third in a production model. This assembly of design elements provides a project flow that leaves little to be interpreted and is suitable for small design teams while still flexible enough to be applied to diverse robotics projects. This thesis provides three case studies analyzing the application of the hybrid design approach mentioned above to robotic system development. The first study showcases a complicated system design with a small development team. The second case is of simpler construction with a smaller developer team. This simpler case better demonstrates the benefits of this hybrid approach in robotic system development due to the comparatively higher speed at which the system matures. The third case study shows how this same proposed approach can be applied to the design of a bottom-up controlled swarm. These case studies are for future designers to reference as examples of the hybrid design methodology in application, and what can happen when there is a lack of feedback in design. This proposed hybrid design method can encourage design practices in new engineers that translate better to industrial applications, and therefore encourage faster integration of new engineers into established design engineering practices

Towards temporal verification of swarm robotic systems

A robot swarm is a collection of simple robots designed to work together to carry out some task. Such swarms rely on the simplicity of the individual robots; the fault tolerance inherent in having a large population of identical robots; and the self-organised behaviour of the swarm as a whole. Although robot swarms present an attractive solution to demanding real-world applications, designing individual control algorithms that can guarantee the required global behaviour is a difficult problem. In this paper we assess and apply the use of formal verification techniques for analysing the emergent behaviours of robotic swarms. These techniques, based on the automated analysis of systems using temporal logics, allow us to analyse whether all possible behaviours within the robot swarm conform to some required specification. In particular, we apply model-checking, an automated and exhaustive algorithmic technique, to check whether temporal properties are satisfied on all the possible behaviours of the system. We target a particular swarm control algorithm that has been tested in real robotic swarms, and show how automated temporal analysis can help to refine and analyse such an algorithm. © 2012 Elsevier B.V. All rights reserved