Social Navigation -Identifying Robot Navigation Patterns in a Path Crossing Scenario

Christina Lichtenthäler (1) , Annika Peters , Sascha Griffiths (2) , Alexandra Kirsch (1, 3, 4)

1 Intelligent Autonomous Systems
2 Queen Mary University of London - Department of Computer Science
3 Human-Computer Interaction and Artificial Intelligence
4 Institute for Advanced Studies

The work at hand addresses the question: What kind of navigation behavior do humans expect from a robot in a path crossing scenario? To this end, we developed the " Inverse Oz of Wizard " study design where participants steered a robot in a scenario in which an instructed person is crossing the robot's path. We investigated two aspects of robot behavior: (1) what are the expected actions? and (2) can we determine the expected action by considering the spatial relationship? The overall navigation strategy, that was performed the most, was driving straight towards the goal and either stop when the person and the robot came close or drive on towards the goal and pass the path of the person. Furthermore, we found that the spatial relationship is significantly correlated with the performed action and we can precisely predict the expected action by using a Support Vector Machine.

Mots clés: social navigation; human-robot interaction; spatial relationship

Domaines: Intelligence artificielle [cs.AI]; Interface homme-machine [cs.HC]; Robotique [cs.RO]

Christina Lichtenthäler, Annika Peters, Sascha Griffiths, Alexandra Kirsch. Social Navigation -Identifying Robot Navigation Patterns in a Path Crossing Scenario. International Conference on Social Robotics (ICSR), 2013, Bristol, United Kingdom. ⟨hal-01684309⟩