Mobile robot path planning based on social interaction space in social environment

摘要

A key skill for mobile robots is the ability to avoid obstacles and efficiently plan a path in their environment. Mobile robot path planning in social environment must not only consider task constraints, such as minimizing the distance traveled to a goal, but also social conventions, such as keeping a comfortable distance from humans. An efficient framework for mobile robots in social environment is proposed in this study. The framework takes into account task constraints and social conventions for path planning. Social conventions incorporate information on human states (position, orientation, and motion) and social interactions in modeling social interaction space. The two-dimensional asymmetric Gaussian function is used to compute the cost of points in social interaction space. The framework integrates the social interaction space into path planning based on A* algorithm, which allows mobile robots to bypass humans in a manner that makes humans feel safe and comfortable. The proposed method verified its effectiveness through simulation and experimental results.