Following Is All You Need: Robot Crowd Navigation Using People As Planners
By: Yuwen Liao , Xinhang Xu , Ruofei Bai and more
Potential Business Impact:
Robot follows people to navigate crowds safely.
Navigating in crowded environments requires the robot to be equipped with high-level reasoning and planning techniques. Existing works focus on developing complex and heavyweight planners while ignoring the role of human intelligence. Since humans are highly capable agents who are also widely available in a crowd navigation setting, we propose an alternative scheme where the robot utilises people as planners to benefit from their effective planning decisions and social behaviours. Through a set of rule-based evaluations, we identify suitable human leaders who exhibit the potential to guide the robot towards its goal. Using a simple base planner, the robot follows the selected leader through shorthorizon subgoals that are designed to be straightforward to achieve. We demonstrate through both simulated and real-world experiments that our novel framework generates safe and efficient robot plans compared to existing planners, even without predictive or data-driven modules. Our method also brings human-like robot behaviours without explicitly defining traffic rules and social norms. Code will be available at https://github.com/centiLinda/PeopleAsPlanner.git.
Similar Papers
A Lightweight Crowd Model for Robot Social Navigation
Robotics
Robots safely move through crowds without getting stuck.
A Hybrid Approach to Indoor Social Navigation: Integrating Reactive Local Planning and Proactive Global Planning
Robotics
Robot learns to walk through crowds safely.
Learning Social Heuristics for Human-Aware Path Planning
Robotics
Robots learn to join lines politely.