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Abstract：
Autonomous robots are already present in a variety of domains performing complex tasks. Their deployment in open-ended environments offers endless possibilities. However, there are still risks due to unresolved issues in dependability and trust. Knowledge representation and reasoning provide tools for handling explicit information, endowing systems with a deeper understanding of the situations they face. This article explores the use of declarative knowledge for autonomous robots to represent and reason about their environment, their designs, and the complex missions they accomplish. This information can be exploited at runtime by the robots themselves to adapt their structure or re-plan their actions to finish their mission goals, even in the presence of unexpected events. The primary focus of this article is to provide an overview of popular and recent research that uses knowledge-based approaches to increase robot autonomy. Specifically, the ontologies surveyed are related to the selection and arrangement of actions, representing concepts such as autonomy, planning, or behavior. Additionally, they may be related to overcoming contingencies with concepts such as fault or adapt. A systematic exploration is carried out to analyze the use of ontologies in autonomous robots, with the objective of facilitating the development of complex missions. Special attention is dedicated to examining how ontologies are leveraged in real time to ensure the successful completion of missions while aligning with user and owner expectations. The motivation of this analysis is to examine the potential of knowledge-driven approaches as a means to improve flexibility, explainability, and efficacy in autonomous robotic systems.
摘要：
自主机器人已经存在于执行复杂任务的各种领域中。它们在开放式环境中的部署提供了无限的可能性。然而,由于可靠性和信任方面尚未解决的问题，仍然存在风险。知识表示和推理提供了处理显式信息的工具，赋予系统更深入地了解他们所面临的情况。本文探讨了自主机器人使用陈述性知识来表示和推理其环境，他们的设计，以及他们完成的复杂任务。机器人本身可以在运行时利用这些信息来调整其结构或重新计划其行动以完成其任务目标。即使是在有意外事件的情况下.本文的主要重点是提供使用基于知识的方法来提高机器人自主性的流行和最新研究的概述。具体来说,所调查的本体与动作的选择和安排有关，代表自治等概念，规划,或行为。此外,它们可能与克服故障或适应等概念的突发事件有关。进行了系统的探索，以分析自主机器人中本体的使用，目的是促进复杂任务的发展。特别关注的是，研究如何实时利用本体，以确保成功完成任务，同时符合用户和所有者的期望。这种分析的动机是研究知识驱动的方法作为提高灵活性的手段的潜力，可解释性,以及自主机器人系统的功效。
