The Immune System: the ultimate fractionated cyber-physical system

In this little vision paper we analyze the human immune system from a computer science point of view with the aim of understanding the architecture and features that allow robust, effective behavior to emerge from local sensing and actions. We then recall the notion of fractionated cyber-physical systems, and compare and contrast this to the immune system. We conclude with some challenges.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455

Game Theory Models for Multi-Robot Patrolling of Infraestructures

Abstract This work is focused on the problem of performing multi‐robot patrolling for infrastructure security applications in order to protect a known environment at critical facilities. Thus, given a set of robots and a set of points of interest, the patrolling task consists of constantly visiting these points at irregular time intervals for security purposes. Current existing solutions for these types of applications are predictable and inflexible. Moreover, most of the previous centralized and deterministic solutions and only few efforts have been made to integrate dynamic methods. Therefore, the development of new dynamic and decentralized collaborative approaches in order to solve the aforementioned problem by implementing learning models from Game Theory. The model selected in this work that includes belief‐based and reinforcement models as special cases is called Experience‐Weighted Attraction. The problem has been defined using concepts of Graph Theory to represent the environment in order to work with such Game Theory techniques. Finally, the proposed methods have been evaluated experimentally by using a patrolling simulator. The results obtained have been compared with previous availabl

Multi-Agent Persistent Task Performance

A method to control a system of robots to persistently perform a task while operating under a constraint such as battery life is presented. Persistently performing a task is defined as continuously executing the task without a break or stopping due to low battery constraints or lack of capabilities of a particular agent. If an agent is no longer able to execute the task it must be replaced by one that can continue the execution of the task. This is achieved through the utilization of two distinctions of agent roles: workers and helpers. This method is focused on addressing problems that require task handoffs where a second robot physically replaces a robot that has run low on battery. The worker agents are assigned the tasks, and perform the tasks until the constraint prevents further performance. Once a worker agent has reached a low battery threshold a task handoff is performed with a helper agent. This method utilizes a proactive approach in performing these handoffs by predicting the time and place that a worker will reach a low battery threshold and need to perform a handoff. This decreases the time necessary to respond to a low battery in these problems compared to prior developed reactive methods. As a result the total time needed by the multi agent team to complete a set of tasks is decreased. In this paper, the method is demonstrated utilizing a physics based simulator to model the behavior of the multi agent team. Experiments are run over three standard problems requiring agent task handoffs: sentry, inspection, and coverage. These demonstrate the effectiveness of the method when compared against the existing reactive methods

Distributed approach for coverage and patrolling missions with a team of heterogeneous aerial robots under communication constraints

Using aerial robots in area coverage applications is an emerging topic. These applications need a coverage path planning algorithm and a coordinated patrolling plan. This paper proposes a distributed approach to coordinate a team of heterogeneous UAVs cooperating efficiently in patrolling missions around irregular areas, with low communication ranges and memory storage requirements. Hence it can be used with small‐scale UAVs with limited and different capabilities. The presented system uses a modular architecture and solves the problem by dividing the area between all the robots according to their capabilities. Each aerial robot performs a decomposition based algorithm to create covering paths and a ’one‐to‐one’ coordination strategy to decide the path segment to patrol. The system is decentralized and fault‐tolerant. It ensures a finite time to share information between all the robots and guarantees convergence to the desired steady state, based on the maximal minimum frequency criteria. A set of simulations with a team of quad‐rotors is used to validate the approach

Deployable Payloads with Starbug

We explore the range of wide field multi-object instrument concepts taking advantage of the unique capabilities of the Starbug focal plane positioning concept. Advances to familiar instrument concepts, such as fiber positioners and deployable fiber-fed IFUs, are discussed along with image relays and deployable active sensors. We conceive deployable payloads as components of systems more traditionally regarded as part of telescope systems rather than instruments - such as adaptive optics and ADCs. Also presented are some of the opportunities offered by the truly unique capabilities of Starbug, such as microtracking to apply intra-field distortion correction during the course of an observation.Comment: 12 pages, 8 figures, to be published in Proc. SPIE 6273 "Opto-Mechanical Technologies for Astronomy