Intelligence and Motion Models of Continuum Robots: an Overview
<|reference_start|>Intelligence and Motion Models of Continuum Robots: an Overview: Many technical solutions are bio-inspired. Octopus-inspired robotic arms belong to continuum robots which are used in minimally invasive surgery or for technical system restoration in areas difficult-toaccess. Continuum robot missions are bounded with their motions, whereby the motion of the robots is controlled by humans via wireless communication. In case of a lost connection, robot autonomy is required. Distributed control and distributed decision-making mechanisms based on artificial intelligence approaches can be a promising solution to achieve autonomy of technical systems and to increase their resilience. However these methods are not well investigated yet. Octopuses are the living example of natural distributed intelligence but their learning and decision-making mechanisms are also not fully investigated and understood yet. Our major interest is investigating mechanisms of Distributed Artificial Intelligence as a basis for improving resilience of complex systems. We decided to use a physical continuum robot prototype that is able to perform some basic movements for our research. The idea is to research how a technical system can be empowered to combine movements into sequences of motions by itself. For the experimental investigations a suitable physical prototype has to be selected, its motion control has to be implemented and automated. In this paper, we give an overview combining different fields of research, such as Distributed Artificial Intelligence and continuum robots based on 98 publications. We provide a detailed description of the basic motion control models of continuum robots based on the literature reviewed, discuss different aspects of autonomy and give an overview of physical prototypes of continuum robots.<|reference_end|>
@article{shamilyan2024intelligence,
    title={Intelligence and Motion Models of Continuum Robots: an Overview},
    author={Oxana Shamilyan, Ievgen Kabin, Zoya Dyka, Oleksandr Sudakov, Andrii
  Cherninskyi, Marcin Brzozowski and Peter Langendoerfer},
    journal={IEEE Access, vol. 11, pp. 60988-61003, 2023},
    year={2024},
    doi={10.1109/ACCESS.2023.3286300},
    archivePrefix={arXiv},
    eprint={2404.06171},
    primaryClass={cs.RO}
}