Abstract
In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI) using a well-established Qualitative Trajectory Calculus (QTC) to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to utilise QTC as a state descriptor and model HRSI as a probabilistic sequence of such states. Apart from the sole direction of movements of human and robot modelled by QTC, attributes of HRSI like proxemics and velocity profiles play vital roles for the modelling and generation of HRSI behaviour. In this paper, we particularly present how the concept of proxemics can be embedded in QTC to facilitate richer models. To facilitate reasoning on HRSI with qualitative representations, we show how we can combine the representational power of QTC with the concept of proxemics in a concise framework, enriching our probabilistic representation by implicitly modelling distances. We show the appropriateness of our sequential model of QTC by encoding different HRSI behaviours observed in two spatial interaction experiments. We classify these encounters, creating a comparative measurement, showing the representational capabilities of the model.
Highlights
Used research and commercial robots are able to navigate safely through their environment, avoiding static and dynamic obstacles
This paper offers a comprehensive overview of the Qualitative Trajectory Calculus (QTC)-based probabilistic sequential representation utilising the Hidden Markov Model (HMM), and focuses on its specific adoptions for the encoding of Human-Robot Spatial Interaction (HRSI) using real-world data
In this work we presented a HMM-based probabilistic sequential representation of HRSI utilising
Summary
Used research and commercial robots are able to navigate safely through their environment, avoiding static and dynamic obstacles. Mere obstacle avoidance is not sufficient in those situations because humans have special needs and requirements to feel safe and comfortable around robots. Human-Robot Spatial Interaction (HRSI) is the study of joint movement of robots and humans through space and the social signals governing these interactions. It is concerned with the investigation of models of the ways humans and robots manage their motions in vicinity to each other. These encounters might, for example, be so-called pass-by situations where human and robot aim to pass through a corridor trying to circumvent each other given spatial constraints. Our work aims to equip a mobile robot with understanding of such HRSI situations and enable it to act
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