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.
The orchestration and controlling of groups of robots, i.e., programming ensembles, is a complicated task to do. Deciding and defining what the ensemble needs to do in which order often requires in-depth problem domain specific knowledge. Further, an ensemble programmer needs to put much effort into the design, implementation, and evaluation of distributed algorithms to coordinate multi-robot executions. Most commonly, expertise for the problem domain and programming knowledge is not united in the same person. To tackle this, we propose Maple, an approach for a Multi-Agent Programming Language for Ensembles. Using Maple simplifies an ensemble programmer's typical work-flow by providing generalized solutions for solving technical tasks in ensemble programming. Maple is a graphical ensemble programming language based on the formalism of hierarchical task networks that enables the online generation of ensemble programs. Maple also enables non-technical domain experts to generate ensemble programs for specific use-cases.
Deadlocks represent situations in which two participants are waiting for each other to finish an activity so that neither of them will ever finish. Deadlocks can occur in complex computer-integrated systems, such as flexible and selforganizing production systems. As deadlocks bring production to halt, methods for deadlock control in production systems are widely studied. Yet most algorithms proposed are not suited for the use in decentral multi-agent systems, as they require central control or can not handle concurrency. Other algorithms can be used in a decentral fashion but assume that only one type of product will be manufactured at a time. But in times of mass customization, where customers choose a product from a variety of options, support for several product types is required. To meet both the requirements of mass customization and decentral multi-agent systems, we present a new decentralized approach for avoiding deadlocks in a self-organizing production cell, where several types of products are being manufactured in parallel. Our approach is based solely on local knowledge and does not assume central control. We evaluate our approach in terms of effectiveness and message overhead to conclude that it avoids starvation and deadlocks with a reasonable message overhead.
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