The presented ontological model and methods for conditional and unconditional diagnostics is used to establish cause-and-effect relationships between observed failures and the malfunctions that cause them and provides an effective basis for activating and utilizing the intelligent control system's rich algorithm databases at all levels of the control hierarchy to support increased adaptability.
A new paradigm is identified for the development of a promising class of autonomous robotic systems with increased fault tolerance and, consequently, adaptability through the use of an ontological model used to establish cause-and-effect relationships between observed failures and the malfunctions that cause them.
Y. A. Bykovtsev, V. Lokhin, S. V. Manko et al.· Russian Technological Journa...· 1 citation
Robots are being deployed for an increasingly diverse set of purposes, from industrial manufacturing to delivery, inspection, and surgical assistance, and the systems entering these roles are markedly more capable than earlier generations, utilizing learned perception, language-based planning, and multi-sensor input. T...
Karthik Rengarajan, Siddharth Pokuri, J. Gao· International Conference on...· 0 citations
The main contribution of this paper is to present a system partitioning criterion, i.e. how to divide the control authority of the different subsystems in order to prevent a single failure from triggering a chain of system failures.
Lina M. Mahmoud, M. Saleh, N. H. Abbas· Jurnal Engineering· 0 citations
This study introduces an innovative framework for anomaly detection and handling in multi-robot collaboration within scientific laboratories, addressing challenges posed by complex procedures and precision equipment. We propose a hierarchical approach utilizing large language models (LLMs) for task planning, action dec...
Yang Yang, Jian-Kun Yang, Hai-Bo Lu et al.· IEEE Transactions on Automat...· 0 citations
Results indicate that A* fails to perform well in dynamic environments and performs nearly optimally in static environments, while APF-D and D* Lite adapt to changes in the environment much better.
Prathyusha Vinukonda, V. Manikandan· Robotics· 0 citations
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