Skip to Main content Skip to Navigation
Conference papers

Socially Compliant Navigation in Dense Crowds

Roman Bresson 1 Jacques Saraydaryan 1 Julie Dugdale 2 Anne Spalanzani 1
1 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
2 HAwAI - Human Aware Artificial Intelligence
LIG - Laboratoire d'Informatique de Grenoble
Abstract : 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.
Document type :
Conference papers
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download
Contributor : Julie Dugdale Connect in order to contact the contributor
Submitted on : Thursday, April 11, 2019 - 9:43:29 AM
Last modification on : Wednesday, November 3, 2021 - 7:30:30 AM


Files produced by the author(s)




Roman Bresson, Jacques Saraydaryan, Julie Dugdale, Anne Spalanzani. Socially Compliant Navigation in Dense Crowds. IV 2019 - 30th IEEE Intelligent Vehicles Symposium, Jun 2019, Paris, France. pp.64-69, ⟨10.1109/IVS.2019.8814288⟩. ⟨hal-02096006⟩



Les métriques sont temporairement indisponibles