Karwowski Jarosław, Szynkiewicz Wojciech, Niewiadomska-Szynkiewicz Ewa
Institute of Control and Computation Engineering, Warsaw University of Technology, 00-665 Warsaw, Poland.
Sensors (Basel). 2024 Apr 27;24(9):2794. doi: 10.3390/s24092794.
Navigation lies at the core of social robotics, enabling robots to navigate and interact seamlessly in human environments. The primary focus of human-aware robot navigation is minimizing discomfort among surrounding humans. Our review explores user studies, examining factors that cause human discomfort, to perform the grounding of social robot navigation requirements and to form a taxonomy of elementary necessities that should be implemented by comprehensive algorithms. This survey also discusses human-aware navigation from an algorithmic perspective, reviewing the perception and motion planning methods integral to social navigation. Additionally, the review investigates different types of studies and tools facilitating the evaluation of social robot navigation approaches, namely datasets, simulators, and benchmarks. Our survey also identifies the main challenges of human-aware navigation, highlighting the essential future work perspectives. This work stands out from other review papers, as it not only investigates the variety of methods for implementing human awareness in robot control systems but also classifies the approaches according to the grounded requirements regarded in their objectives.
导航是社交机器人技术的核心，它使机器人能够在人类环境中无缝导航和交互。具备人类感知能力的机器人导航的主要重点是将周围人类的不适感降至最低。我们的综述探讨了用户研究，研究导致人类不适的因素，以确立社交机器人导航要求的基础，并形成应由综合算法实现的基本需求分类法。本调查还从算法角度讨论了具备人类感知能力的导航，回顾了社交导航不可或缺的感知和运动规划方法。此外，该综述研究了有助于评估社交机器人导航方法的不同类型的研究和工具，即数据集、模拟器和基准测试。我们的调查还确定了具备人类感知能力的导航的主要挑战，突出了未来工作的重要观点。这项工作与其他综述论文不同，因为它不仅研究了在机器人控制系统中实现人类感知的各种方法，还根据其目标中所考虑的既定要求对这些方法进行了分类。
