A Software Architecture for Adaptive Modular Sensing Systems

In this thesis, a novel software architecture and knowledge representation scheme is described that facilitates the combination and reconfiguration of modular sensor and actuator components, termed transducer interface modules (TIMs), to produce flexible modular sensor systems. Each TIM provides a core sensing or actuation functionality. A composite sensor is able to automatically determine its overall geometry and assume an appropriate collective identity, and if reconfigured, may then assume a different identity to match its new geometry. In current practice, a fixed combination of sensors and actuators is typically utilized, and is tailored to a specific application. Such systems cannot be cheaply or quickly reconfigured to handle a change in process requirements. Domains that may benefit from easily reconfigurable modular sensing systems include flexible inspection, mobile robotics, surveillance, and even space exploration. The software architecture is distributed, and is comprised of six layers where the implementation of each layer is encapsulated from the layer above, to which it provides service. The use of a distributed and layered architecture promotes scalability, mitigates against a single point of failure, and enables each layer to be easily implemented, modified, and debugged independently of the others. The modularization of the software architecture is further facilitated through the utilization of a pre-emptive real-time operating system, which enables the concurrent execution of the various software components specific to the architecture that implement the services provided within most of its layers. Among the layers comprising the software architecture is a virtual machine layer, which implements a lightweight, architecture-specific version of Sun Microsystems’ Java Virtual Machine that runs on top of the real-time operating system. The integration of a virtual machine enables the platform-independent template algorithms utilized at the composition layer to be written once and executed on any TIM irrespective of its underlying hardware architecture. These template algorithms are unique to this software architecture and provide intelligence to a set of heterogeneous TIMs, enabling them to collaborate and behave as a single entity termed a logical module. The evaluation of the software architecture consists of performing multiple runs of two tests in which select sensors and actuators are associated with TIMs that are then allowed to interact in order to form a logical entity. The first test evaluates the behaviour of a logical module in which the constituent TIMs interact entirely through wireless communication. The second test evaluates the behaviour of a logical module in which the constituent TIMs are physically connected in various orientations, and interact through both wireless communication as well as through their physically connected faces. In both tests, correct behaviour was exhibited. However, the performance and scalability of the architecture was somewhat restricted by the limited processing and memory resources present in the current implementation of the TIMs. The design of the software architecture facilitates easy portability between embedded platforms and scales with increasing hardware capability. Therefore, utilization of future TIM hardware variations possessing increased processing and memory resources will reduce the latencies introduced throughout the architecture and lead to tangible improvements in its performance

Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

Toward a unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning

The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Known environmental features, such as signs, buildings, terrain height variation, and magnetic anomalies, may or may not be available for positioning. The system could be stationary, carried by a pedestrian, or on any type of land, sea, or air vehicle. Furthermore, for many applications, the environment and host behavior are subject to change. A multi-sensor solution is thus required. The expert knowledge problem is compounded by the fact that different modules in an integrated navigation system are often supplied by different organizations, who may be reluctant to share necessary design information if this is considered to be intellectual property that must be protected

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

Flora robotica -- An Architectural System Combining Living Natural Plants and Distributed Robots

Key to our project flora robotica is the idea of creating a bio-hybrid system of tightly coupled natural plants and distributed robots to grow architectural artifacts and spaces. Our motivation with this ground research project is to lay a principled foundation towards the design and implementation of living architectural systems that provide functionalities beyond those of orthodox building practice, such as self-repair, material accumulation and self-organization. Plants and robots work together to create a living organism that is inhabited by human beings. User-defined design objectives help to steer the directional growth of the plants, but also the system's interactions with its inhabitants determine locations where growth is prohibited or desired (e.g., partitions, windows, occupiable space). We report our plant species selection process and aspects of living architecture. A leitmotif of our project is the rich concept of braiding: braids are produced by robots from continuous material and serve as both scaffolds and initial architectural artifacts before plants take over and grow the desired architecture. We use light and hormones as attraction stimuli and far-red light as repelling stimulus to influence the plants. Applied sensors range from simple proximity sensing to detect the presence of plants to sophisticated sensing technology, such as electrophysiology and measurements of sap flow. We conclude by discussing our anticipated final demonstrator that integrates key features of flora robotica, such as the continuous growth process of architectural artifacts and self-repair of living architecture.Comment: 16 pages, 12 figure

A Software Suite for the Control and the Monitoring of Adaptive Robotic Ecologies

Adaptive robotic ecologies are networks of heterogeneous robotic devices (sensors, actuators, automated appliances) pervasively embedded in everyday environments, where they learn to cooperate towards the achievement of complex tasks. While their flexibility makes them an increasingly popular way to improve a system’s reliability, scalability, robustness and autonomy, their effective realisation demands integrated control and software solutions for the specification, integration and management of their highly heterogeneous and computational constrained components. In this extended abstract we briefly illustrate the characteristic requirements dictated by robotic ecologies, discuss our experience in developing adaptive robotic ecologies, and provide an overview of the specific solutions developed as part of the EU FP7 RUBICON Project