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KRIOTA: A framework for Knowledge-management of dynamic Reference Information and Optimal Task Assignment in hybrid edge–cloud environments to support situation-aware robot-assisted operations
Journal article   Peer reviewed

KRIOTA: A framework for Knowledge-management of dynamic Reference Information and Optimal Task Assignment in hybrid edge–cloud environments to support situation-aware robot-assisted operations

Muhammad Aufeef Chauhan, Muhammad Ali Babar and Haifeng Shen
Future generation computer systems, Vol.160, pp.489-504
11/2024
DOI: https://doi.org/10.1016/j.future.2024.06.014
Appears in  Recent Faculty of Science and Engineering Publications

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Abstract

Autonomous robotic system (ARS) Dynamic Reference Information (DRI) Dynamic tasks allocation Edge–cloud environment Knowledge management
Enabling an autonomous robotic system (ARS) to be aware of its operating environment can equip the system to deal with unknown and uncertain situations. While several conceptual models have been proposed to establish the fundamental concepts of situational awareness, it remains a challenge to make an ARS situation aware, in particular using a combination of low-cost resource-constraint robots at the tactical edge and powerful remote cloud nodes. This paper proposes a dynamic reference information (DRI) based knowledge management and optimal task assignment framework that manages knowledge extracted from DRI to assess the current situation as per given mission objectives and assigns tasks to different computing nodes, which include a combination of edge robots, edge computing nodes and cloud-hosted services. The proposed framework is referred to as KRIOTA. The framework has been designed using an architecture-centric approach. We have designed ontologies to classify and structure different elements of DRI hierarchically and associate the processing components of an ARS with the DRI. We have devised algorithms for the ARS to optimally assign tasks to relevant processing components on robots, edge computing nodes and cloud-hosted services for adaptive behaviour. We have evaluated the framework by demonstrating its implementation in a testbed named RoboPatrol. We have also demonstrated the performance, effectiveness and feasibility of the KRIOTA framework.

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