Look Before You Leap: Socially Acceptable High-Speed Ground Robot Navigation in Crowded Hallways

To operate safely and efficiently, autonomous warehouse/delivery robots must be able to accomplish tasks while navigating in dynamic environments and handling the large uncertainties associated with the motions/behaviors of other robots and/or humans. A key scenario in such environments is the hallway problem, where robots must operate in the same narrow corridor as human traffic going in one or both directions. Traditionally, robot planners have tended to focus on socially acceptable behavior in the hallway scenario at the expense of performance. This paper proposes a planner that aims to address the consequent "robot freezing problem" in hallways by allowing for "peek-and-pass" maneuvers. We then go on to demonstrate in simulation how this planner improves robot time to goal without violating social norms. Finally, we show initial hardware demonstrations of this planner in the real world, along with a novel STAR (Socially Trained Agile Robot) platform designed with human comfort in mind.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801967
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
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article

Look Before You Leap: Socially Acceptable High-Speed Ground Robot Navigation in Crowded Hallways

Jonathan P. How, Lakshay Sharma, Xiaoyi Cai, Nicolaniello Buono et al.
Robotics and Automated Systems
article

Look Before You Leap: Socially Acceptable High-Speed Ground Robot Navigation in Crowded Hallways

Jonathan P. How, Lakshay Sharma, Xiaoyi Cai, Nicolaniello Buono, Ashton Flather
article en

Abstract

To operate safely and efficiently, autonomous warehouse/delivery robots must be able to accomplish tasks while navigating in dynamic environments and handling the large uncertainties associated with the motions/behaviors of other robots and/or humans. A key scenario in such environments is the hallway problem, where robots must operate in the same narrow corridor as human traffic going in one or both directions. Traditionally, robot planners have tended to focus on socially acceptable behavior in the hallway scenario at the expense of performance. This paper proposes a planner that aims to address the consequent "robot freezing problem" in hallways by allowing for "peek-and-pass" maneuvers. We then go on to demonstrate in simulation how this planner improves robot time to goal without violating social norms. Finally, we show initial hardware demonstrations of this planner in the real world, along with a novel STAR (Socially Trained Agile Robot) platform designed with human comfort in mind.

Massachusetts Institute of Technology (US)
Openalex Percentile: Top 71%
Robotics and Automated Systems
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