Abstract
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.
Highlights
Path planning is a key technique of mobile robot navigation1 and a hot issue in mobile robot research.2 The ability to safely navigate in crowded and dynamic environments becomes crucial for mobile robots employed in indoor environments, such as shopping malls, museums, or schools.3 In these environments, mobile robots often need to follow social rules when they encounter humans in certain places, such as corridors
The framework for the mobile robot path planning proposed in this study considers task constraints and social conventions, which differs from traditional techniques4–14 that only consider task
To enhance the navigability of mobile robots in social environments, we developed a human-comfortable safety framework that models a social interaction space using a two-dimensional asymmetric Gaussian function based on task constraints and social conventions
Summary
Path planning is a key technique of mobile robot navigation1 and a hot issue in mobile robot research.2 The ability to safely navigate in crowded and dynamic environments becomes crucial for mobile robots employed in indoor environments, such as shopping malls, museums, or schools.3 In these environments, mobile robots often need to follow social rules when they encounter humans in certain places, such as corridors. To enhance the navigability of mobile robots in social environments, we developed a human-comfortable safety framework that models a social interaction space using a two-dimensional asymmetric Gaussian function based on task constraints and social conventions.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
