The proposed algorithm incorporates a similarity cost term that pushes the planner to generate a path with lower similarity to the unintended path (in red), and it generates the dark green path at the top, which decreases the confusion for the observer, and improves the legibility of the robot’s motion.
With the increasing presence of social robots in various environments and applications, there is an increasing need for these robots to exhibit socially-compliant behaviors. Legible motion, characterized by the ability of a robot to clearly and quickly convey intentions and goals to the individuals in its vicinity, through its motion, holds significant importance in this context. This will improve the overall user experience and acceptance of robots in human environments. In this paper, we introduce a novel approach to incorporate legibility into local motion planning for mobile robots. This can enable robots to generate legible motions in real-time and dynamic environments. To demonstrate the effectiveness of our proposed methodology, we also provide a robotic stack designed for deploying legibility-aware motion planning in a social robot, by integrating perception and localization components.
@misc{amirian2024legibot,
title={Legibot: Generating Legible Motions for Service Robots Using Cost-Based Local Planners},
author={Javad Amirian and Mouad Abrini and Mohamed Chetouani},
year={2024},
eprint={2404.05100},
archivePrefix={arXiv},
primaryClass={cs.RO}
}