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首页> 外文期刊>Pattern recognition letters >Socially aware robot navigation system in human-populated and interactive environments based on an adaptive spatial density function and space affordances
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Socially aware robot navigation system in human-populated and interactive environments based on an adaptive spatial density function and space affordances

机译：基于自适应空间密度函数和空间承受能力的人机交互环境中具有社会意识的机器人导航系统

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Traditionally robots are mostly known by society due to the wide use of manipulators, which are generally placed in controlled environments such as factories. However, with the advances in the area of mobile robotics, they are increasingly inserted into social contexts, i.e., in the presence of people. The adoption of socially acceptable behaviours demands a trade-off between social comfort and other metrics of efficiency. For navigation tasks, for example, humans must be differentiated from other ordinary objects in the scene. In this work, we propose a novel human-aware navigation strategy built upon the use of an adaptive spatial density function that efficiently cluster groups of people according to their spatial arrangement. Space affordances are also used for defining potential activity spaces considering the objects in the scene. The proposed function defines regions where navigation is either discouraged or forbidden. To implement a socially acceptable navigation, the navigation architecture combines a probabilistic roadmap and rapidly-exploring random tree path planners, and an adaptation of the elastic band algorithm. Trials in real and simulated environments carried out demonstrate that the use of the clustering algorithm and social rules in the navigation architecture do not hinder the navigation performance. (C) 2018 Published by Elsevier B.V.
机译：传统上，由于机械手的广泛使用，机器人通常是社会所熟知的，这些机械手通常被放置在诸如工厂之类的受控环境中。但是，随着移动机器人技术领域的进步，它们越来越多地插入到社会环境中，即在人们在场的情况下。采用社会上可接受的行为需要在社会舒适度和其他效率指标之间进行权衡。例如，对于导航任务，必须将人与场景中的其他普通对象区分开。在这项工作中，我们提出了一种新的基于人类的导航策略，该策略建立在自适应空间密度函数的使用之上，该函数可以根据人群的空间布置有效地对其进行聚类。空间馈赠还用于考虑场景中的对象来定义潜在的活动空间。提议的功能定义了不鼓励或禁止导航的区域。为了实现社会上可接受的导航，导航体系结构将概率路线图和快速探索的随机树路径规划器以及弹性带算法的改编结合在一起。在真实和模拟环境中进行的试验表明，在导航体系结构中使用聚类算法和社会规则不会妨碍导航性能。 （C）2018由Elsevier B.V.发布

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