Towards Self-Organizing Swarms of Reconfigurable Self-Aware Robots

Kosak, Oliver; Wanninger, Constantin; Angerer, Alfred; Hoffmann, Alwin; Schiendorfer, Alexander; Seebach, Hella

doi:10.1109/fas-w.2016.52

Cited by 9 publications

(12 citation statements)

References 19 publications

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“…From an observing perspective, many inventions currently often address similar problems (or tasks) in different granularity, being adapted to diverse environmental conditions (e.g., space [28], airborne [12,14], on-ground [13], water surface level [18], or underwater [19]), application scenarios (cf. above, e.g., environmental research [18,19,20], search and rescue [13,14,28], distributed surveillance [15,16,29,30], or major catastrophes [12,31,32]), the systems’ configurations (homogeneous [18,22,33] or heterogeneous [13,14,19,23,31] distribution of capabilities among robots), and coordination technologies (implicitly done with, e.g., swarm algorithms [18,19,23], explicitly done with, e.g., multiagent technologies [13,14,31] or manual coordination [20]). All these aspects lead to a high diversity of approaches (cf.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, with their design time homogeneity, robots in multipotent systems easily can compensate for each other in case of failures, as can be done in homogeneous systems. Our approach therefore aims at developing a reference system architecture for ensembles consisting of multipotent robots to handle the broad class of ScORe missions [31], involving search (S), continuously observe (cO), and react (Re) tasks. This broad system class subsumes other types of applications, such as search and rescue [11], environmental research [18,19,39], distributed surveillance of critical infrastructure [15,16,17], or dealing with major catastrophic incidents [12].…”

Section: Introductionmentioning

confidence: 99%

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Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles

Kosak

Wanninger

Hoffmann

et al. 2018

Sensors

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles

Kosak

Wanninger

Hoffmann

et al. 2018

Sensors

Self Cite

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“…Current developments indicate their usefulness in versatile forms of applications which offer the potential to improve human life in a multitude of different areas. From applications simply dedicated to public amusement during mass events (e.g., at the Olympic Winter Games 2018 in Pyeongchang, or CES 2018 in Las Vegas) over intensified use for supporting different research areas (e.g., environmental research [1]- [4]) up to mission critical tasks like supporting rescue forces in dangerous environments [5]- [8]. Especially systems including unmanned aerial vehicles (UAVs) experience an upswing.…”

Section: Introductionmentioning

confidence: 99%

“…Due to that need for specialization, every time an existing application is modified or a new use case is found where mobile robots may help with, new robots offering the particular capabilities have to be designed, constructed, programmed, and deployed. The approach proposed in our previous work [8], [11] aims at overcoming this limitation. By separating capabilities from robots, we introduce a new degree of flexibility for adapting to changing task requirements or even application requirements.…”

Section: Introductionmentioning

confidence: 99%

Self-Organized Resource Allocation for Reconfigurable Robot Ensembles

Hanke

Kosak

Schiendorfer

et al. 2018

2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)

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Mobile robot systems usually are designed, built, and programmed for dedicated use cases. Consequently, especially for unmanned aerial vehicles diverse applications result in very heterogeneously designed robots. To overcome this need for specialization, we propose to dynamically adapt the robots' capabilities at run-time. This is done by connecting and disconnecting hardware modules providing those capabilities, i.e., re-allocating resources within the robot ensemble. Thereby, no longer individualized robots have to be designed for different tasks. Instead, the system is enabled to adapt its hardware configuration to changing requirements. For calculating necessary adaptations, i.e., solving the resource allocation problem, we propose a heuristic, marketbased approach that exploits the possibility to decompose the resource allocation problem and distributively finds a solution. We show that our approach outperforms a centralized one especially when increasing the problem size in terms of agents, tasks, and relevant capabilities while providing the same quality.

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“…In networks where cameras can change their pose or relocate, it is important to coordinate the cameras so that network goals are met [17,23]. These might include: maximise the number of tracked objects, ensure each target is tracked by k cameras at a time, etc.…”

Section: Networking and Coordinationmentioning

confidence: 99%

The Future of Camera Networks

Esterle

Lewis

McBride³

et al. 2017

Proceedings of the 11th International Conference on Distributed Smart Cameras

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Camera networks become smart when they can interpret video data on board, in order to carry out tasks as a collective, such as target tracking and (re-)identification of objects of interest. Unlike today's deployments, which are mainly restricted to lab settings and highly controlled high-value applications, future smart camera networks will be messy and unpredictable. They will operate on a vast scale, drawing on mobile resources connected in networks structured in complex and changing ways. They will comprise heterogeneous and decentralised aggregations of visual sensors, which will come together in temporary alliances, in unforeseen and rapidly unfolding scenarios. The potential to include and harness citizen-contributed mobile streaming, body-worn video, and robotmounted cameras, alongside more traditional fixed or PTZ cameras, and supported by other non-visual sensors, leads to a number of difficult and important challenges. In this position paper, we discuss a variety of potential uses for such complex smart camera networks, and some of the challenges that arise when staying smart in the presence of such complexity. We present a general discussion on the challenges of heterogeneity, coordination, self-reconfigurability, mobility, and collaboration in camera networks. KEYWORDSfuture camera networks, surveillance, mobile smart cameras, body worn cameras, humans in the loop, distributed control ACM Reference format:

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Towards Self-Organizing Swarms of Reconfigurable Self-Aware Robots

Cited by 9 publications

References 19 publications

Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles

Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles

Self-Organized Resource Allocation for Reconfigurable Robot Ensembles

The Future of Camera Networks

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