ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.

Mobile multirobot systems play an increasing role in many disciplines. Their capabilities can be used, e.g., to transport workpieces in industrial applications or to support operational forces in search and rescue scenarios, among many others. Depending on the respective application, the hardware design and accompanying software of mobile robots are of various forms, especially for integrating different sensors and actuators. Concerning this design, robots of one system compared to each other can be classified to exclusively be either homogeneous or heterogeneous, both resulting in different system properties. While homogeneously configured systems are known to be robust against failures through redundancy but are highly specialized for specific use cases, heterogeneously designed systems can be used for a broad range of applications but suffer from their specialization, i.e., they can only hardly compensate for the failure of one specialist. Up to now, there has been no known approach aiming to unify the benefits of both these types of system. In this paper, we present our approach to filling this gap by introducing a reference architecture for mobile robots that defines the interplay of all necessary technologies for achieving this goal. We introduce the class of robot systems implementing this architecture as multipotent systems that bring together the benefits of both system classes, enabling homogeneously designed robots to become heterogeneous specialists at runtime. When many of these robots work together, we call the structure of this cooperation an ensemble. To achieve multipotent ensembles, we also integrate reconfigurable and self-descriptive hardware (i.e., sensors and actuators) in this architecture, which can be freely combined to change the capabilities of robots at runtime. Because typically a high degree of autonomy in such systems is a prerequisite for their practical usage, we also present the integration of necessary mechanisms and algorithms for achieving the systems’ multipotency. We already achieved the first results with robots implementing our approach of multipotent systems in real-world experiments as well as in a simulation environment, which we present in this paper.

Multi-agent systems can be a viable choice for realizing self-organizing systems consisting of reconfigurable software components. We present a real-world system consisting of heterogeneous air and ground robots whose behavior and coordination is orchestrated by a MAS in a decentralized manner. The system is able to cooperatively transport largescale measuring equipment and is used for environmental observation, such as in-situ measuring of temperature.

Designing complex adaptive systems for real world applications is a delicate challenge, especially when support for humans in crucial situations should be achieved. In this position paper, we propose a multi-agent based approach for physically reconfigurable, heterogeneous robot swarms. These can be deployed when there is a need to search, continuously observe and react, e.g. in disaster scenarios. We show first results that validate the feasibility of our approach.

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This paper describes the use of semantically annotated data for the expression of sensors and actuators with their properties and capabilities. For this purpose, a plug and play mechanism is presented in order to exchange self-descriptions between several hardware devices and then use the established information for the execution of capabilities. For the combination of different capabilities distributed on multiple hardware devices an architecture is presented to link abstract capabilities. These abstract capabilities are initialized through concrete capabilities of the discovered hardware devices by the plug and play mechanism.

Swarm behavior can be very beneficial for real-world robot applications. While analyzing the current state of research, we identified that many studied swarm algorithms foremost aim at modifying the movement vector of the executing robot. In this paper, we demonstrate how we encapsulate this behavior in a general pattern that robots can execute with adjusted parameters for realizing different beneficial swarm algorithms. We integrate the pattern as a virtual swarm capability in our reference architecture for multipotent, reconfigurable multi-robot ensembles and demonstrate its application in proof of concepts. We further illustrate how we can lift the concept of virtual capabilities to also integrate other known approaches for collective system programming as virtual collective capabilities. As an example, we do so by integrating the execution platform for the Protelis aggregate programming language.

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