用本体模型提升机器人语义导航能力，让机器更懂人类环境
Reasoning Systems for Semantic Navigation in Mobile Robots
- 构建基于本体的环境语义模型，融合概念与关系
- 对比两种实现：关系数据库与KnowRob系统，均支持导航决策
- 在真实机器人上验证，适合人机交互场景研究者参考
语义导航是一种将环境语义概念及其关系纳入路径规划的机器人导航范式，有助于人机交互和理解人类环境中的导航目标与任务。该范式需要两个核心组件：环境的语义表示与推理系统。本文聚焦于环境的语义建模，提出两种解决方案：均采用本体模型，分别基于关系数据库和KnowRob实现。两种系统均已集成至语义导航器中，并在定性与定量层面进行比较，最终在移动机器人上完成原型验证。
原文摘要 · Abstract (English)
Semantic navigation is the navigation paradigm in which environmental semantic concepts and their relationships are taken into account to plan the route of a mobile robot. This paradigm facilitates the interaction with humans and the understanding of human environments in terms of navigation goals and tasks. At the high level, a semantic navigation system requires two main components: a semantic representation of the environment, and a reasoner system. This paper is focused on develop a model of the environment using semantic concepts. This paper presents two solutions for the semantic navigation paradigm. Both systems implement an ontological model. Whilst the first one uses a relational database, the second one is based on KnowRob. Both systems have been integrated in a semantic navigator. We compare both systems at the qualitative and quantitative levels, and present an implementation on a mobile robot as a proof of concept.
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