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

Abstract

Abstract. 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.

Hesitation signals in human-robot head-on encounters

“…During the interaction the robot showed two different behaviours, i.e adaptive and non-adaptive velocity control, which was switched at random upon the robots arrival at the kitchen counter. When executing the adaptive behaviour the robot gradually slowed down while approaching the human and stopped before entering the personal zone [1] of the participant to let her/him pass (inspired by findings of [4]). In the non-adaptive behaviour the robot tried to reach the goal as efficient as possible regarding the human as a static obstacle.…”

Robot–City Interaction: Mapping the Research Landscape—A Survey of the Interactions Between Robots and Modern Cities

“…Other works focus on improving the simultaneous localization and navigation through the integration of some a priori knowledge, e.g. some pre-analyzed human behaviors [63,70,77,102] or knowledge from some external sources [7,65,80].…”

“…• mostly social or public interactions, happening in exhibit, passage and special use spaces; • little robot-government interaction (only reported in [63]); • employment of mostly single robots, which do not necessitate data dissemination, due to the focus on performing advanced navigation.…”

A Computational Model of Human-Robot Spatial Interactions Based on a Qualitative Trajectory Calculus

“…To overcome this deficit and to highlight the interaction of the two agents in close vicinity to one another, we aim to model these distances using our HMM-based representation of QTC. Instead of modelling distance explicitly by expanding the QTC-state descriptors and including it as an absolute value, as e.g., suggested by Lichtenthäler et al [17], we aim to model it implicitly and refrain from altering the used calculus to preserve its qualitative nature and the resulting generalisability, and simplicity. We utilise our HMM-based model and different variants of QTC to define transitions between a coarse and fine version of the calculus depending on the distance between human and robot.…”