Department of Electronic Technology, University of Málaga, 29071 Málaga, Spain.
Department of Mechanic Engineering, Computer, and Aerospace Science, University of León, 24007 León, Spain.
Sensors (Basel). 2020 Nov 29;20(23):6822. doi: 10.3390/s20236822.
Social robots, designed to interact and assist people in social daily life scenarios, require adequate path planning algorithms to navigate autonomously through these environments. These algorithms have not only to find feasible paths but also to consider other requirements, such as optimizing energy consumption or making the robot behave in a socially accepted way. Path planning can be tuned according to a set of factors, being the most common path length, safety, and smoothness. This last factor may have a strong relation with energy consumption and social acceptability of produced motion, but this possible relation has never been deeply studied. The current paper focuses on performing a double analysis through two experiments. One of them analyzes energy consumption in a real robot for trajectories that use different smoothness factors. The other analyzes social acceptance for different smoothness factors by presenting different simulated situations to different people and collecting their impressions. The results of these experiments show that, in general terms, smoother paths decrease energy consumption and increase acceptability, as far as other key factors, such as distance to people, are fulfilled.
社交机器人旨在互动并协助人们在社交日常生活场景中，需要足够的路径规划算法来自主导航这些环境。这些算法不仅要找到可行路径，还要考虑其他要求，例如优化能源消耗或使机器人以社会可接受的方式表现。路径规划可以根据一组因素进行调整，其中最常见的因素是路径长度、安全性和平滑度。后一个因素可能与产生的运动的能量消耗和社会可接受性有很强的关系，但这个可能的关系从未被深入研究过。本文重点通过两个实验进行双重分析。其中一个实验分析了在使用不同平滑度因子的轨迹中，实际机器人的能源消耗。另一个实验通过向不同的人展示不同的模拟情况并收集他们的印象，分析了不同平滑度因子的社会可接受性。这些实验的结果表明，在一般情况下，更平滑的路径会降低能耗并提高可接受性，只要满足其他关键因素，如与人的距离。
