论文标题
微创社会导航
Minimally Invasive Social Navigation
论文作者
论文摘要
将移动机器人整合到人类社会中涉及人群导航的基本问题。通过考虑人类在个体水平上的行为来研究这个问题，但是这种表示限制了运动计划算法的计算效率。我们探索将人群作为流场的想法，并根据侵入性的概念提出对路径质量的形式定义。机器人应该试图以一种在其环境中对人类的侵入性最低侵入性的方式进行导航。我们基于此定义开发了一个算法框架，用于路径规划，并提供了表明其有效性的实验结果。这些结果打开了由人群的流场表示动机引起的新算法问题，并且是端到端实施道路的必要步骤。
Integrating mobile robots into human society involves the fundamental problem of navigation in crowds. This problem has been studied by considering the behaviour of humans at the level of individuals, but this representation limits the computational efficiency of motion planning algorithms. We explore the idea of representing a crowd as a flow field, and propose a formal definition of path quality based on the concept of invasiveness; a robot should attempt to navigate in a way that is minimally invasive to humans in its environment. We develop an algorithmic framework for path planning based on this definition and present experimental results that indicate its effectiveness. These results open new algorithmic questions motivated by the flow field representation of crowds and are a necessary step on the path to end-to-end implementations.
