Author/Contact: Lukas Esterle
Abstract
Many autonomous systems are designed and developed to work as a homogenous group and interact with other systems. This requires the developers to consider and foresee these interactions during the development process. Specifically, architectures and system design, communication protocols and interaction mechanisms need to work seamlessly across large numbers of systems. At runtime, systems need to make many different decisions such as decide how to react to their environment, how and with what other systems to interact, as well as what information should be retained and where it should be kept. Cloud computing systems, operating as an additional autonomous system, can provide additional support when respective communication channels are available.
However due to rapidly unfolding situations and constantly changing environments and new systems, including new software and hardware, predicting potential future interactions becomes impossible. Networked autonomous systems therefore need not only be able to detect other systems in their environment but also to interact and integrate with them at runtime even when not being designed for this specific purpose. During runtime, the state of the environment needs to be verified to ensure proper behaviour and correct decisions. Controlling such evolving autonomous systems-of-systems while ensuring the underlying individual goals are still met is another topic of interest in this theme.
To implement Networked Autonomous Systems, we have to consider various areas of research:
- Communication and Networking: In order to communicate with other systems in the environment, networking technologies have to be available. Operating in dynamic environments with potentially changing requirements demands adaptation capabilities on the communication.
- Software Architectures and Software Engineering: Developing new networked autonomous systems asks for novel architectures and even approaches in software engineering. The unpredictable interaction with other systems requires new testing strategies to analyse a wide set of potential situations.
- Self-integration: Systems have to be able to identify and analyse interactions with other systems in the environment. Only by having this information, autonomous networked systems can improve and optimise their own actions in unison with their environment.
- Control: Rapidly unfolding situations require fast responses from novel adaptive and autonomous control mechanisms. While the autonomous systems make decisions, they still need to respond to the environment without bringing themselves or others to harm.
- Emergent Behaviour: When multiple autonomous systems operate in a common environment, certain behaviour can emerge from the respective interactions. An important question is how we can control – e.g. instigate, stop, speed up or slow down the behaviour and/or the respective effects.6. Verification: Verification of desired or undesired states as part of the software engineering process is a standard nowadays. Networked autonomous systems and their potential emergent behaviour pose a special case as their verification needs to be performed as a collective as well as during runtime.
You might be interested to explore more on the topic:
- Rizk, Yara, Mariette Awad, and Edward W. Tunstel. Cooperative heterogeneous multi-robot systems: A survey. ACM Computing Surveys, 52(2):1-31, 2019.
- Bonabeau, Eric, Marco Dorigo, and Guy Théraulaz. From natural to artificial swarm intelligence. Oxford University Press, 1999.
- Khan, Asif, Bernhard Rinner, and Andrea Cavallaro. Cooperative robots to observe moving targets. IEEE Transactions on Cybernetics, 48(1):187-198, 2016.
- Garcıa, Sergio, Claudio Menghi, Patrizio Pelliccione, Thorsten Berger, and Rebekka Wohlrab. An architecture for decentralized, collaborative, and autonomous robots. In Proc. IEEE International Conference on Software Architecture (ICSA), pp. 75-7509. IEEE, 2018.
- Plathottam, Siby Jose, and Prakash Ranganathan. Next generation distributed and networked autonomous vehicles. In Proc. 2018 10th International Conference on Communication Systems & Networks (COMSNETS), pp. 577-582. IEEE, 2018.
ASI Forum board member in charge: Lukas Esterle
Lukas Esterle received his MSc (Dipl.-Ing.) and PhD (Dr.-techn.) from the University of Klagenfurt, Austria in 2010 and 2014 respectively. Afterwards he was a Post-doctoral researcher at Vienna University of Technology before becoming a Marie Skłodowska-Curie fellow at Aston University and the University of Birmingham, UK. In 2019 he joined Aarhus University, Denmark, where he is now an Associate Professor and leads the Autonomous Intelligent Systems research theme. He authored numerous papers, articles and book chapters on computational self-awareness, autonomous and self-adaptive systems, and collaborative behaviour. He is a member of the DIGIT Aarhus University Centre for Digitalisation, Big Data and Data Analytics, the steering committee of the International Conference on Autonomic Computing and Self-organizing Systems (ACSOS), and area chair for IEEE Flagship Conference on Multimedia and Expo (ICME).