Socially Compliant Navigation in Dense Crowds

Roman Bresson1, Jacques Saraydaryan, Julie Dugdale2, Anne Spalanzani3

  • 1Grenoble Alpes University Inria
  • 2Grenoble Alpes University Lig Laboratory
  • 3Inria





09:00 - 14:30 | Sun 9 Jun | Room L213 | SuDT4

HFIV: Human Factors in Intelligent Vehicles

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Navigating in complex and highly dynamic environments such as crowds is still a major challenge for autonomous vehicle such as autonomous wheelchairs or even autonomous cars. This article presents a new way of navigating in crowds by using behavioral clustering for the surrounding agents and representing the crowd as a set of moving polygons. Once the environment has been modelled in this way and the robot has all the information it needs, we then propose a navigation algorithm that is able to guide the vehicle through the scene. The key-points of this algorithm are that (1) it can avoid densely-populated areas in order to minimize the risk of being on a collision course with any of the surrounding dynamic obstacles, (2) it generates socially compliant trajectories.

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