Qualitative Design and Implementation of Human-Robot Spatial Interactions

Bellotto, Nicola; Hanheide, Marc; Weghe, Nico Van de

doi:10.1007/978-3-319-02675-6_33

Cited by 17 publications

(19 citation statements)

References 15 publications

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“…QTC Double Cross = QTCC). Combinations of QTCB and QTCC sequences were then exploited in (Bellotto et al, 2013) to design and implement human-robot spatial interactions with varying degrees of resolution, depending on the scenario and the desired robot's behavior. In all these cases, however, only 2D trajectories have been considered.…”

Section: Introductionmentioning

confidence: 99%

QTC3D: Extending the qualitative trajectory calculus to three dimensions

Mavridis

Bellotto

Iliopoulos

et al. 2015

Information Sciences

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Spatial interactions between agents (humans, animals, or machines) carry information of high value to human or electronic observers. However, not all the information contained in a pair of continuous trajectories is important and thus the need for qualitative descriptions of interaction trajectories arises. The Qualitative Trajectory Calculus (QTC) (Van de Weghe, 2004) is a promising development towards this goal. Numerous variants of QTC have been proposed in the past and QTC has been applied towards analyzing various interaction domains. However, an inherent limitation of those QTC variations that deal with lateral movements is that they are limited to two-dimensional motion; therefore, complex three-dimensional interactions, such as those occurring between flying planes or birds, cannot be captured. Towards that purpose, in this paper QTC3Dis presented: a novel qualitative trajectory calculus that can deal with full three-dimensional interactions. QTC3D is based on transformations of the Frenet-Serret frames accompanying the trajectories of the moving objects. Apart from the theoretical exposition, including definition and properties, as well as computational aspects, we also present an application of QTC3D towards modeling bird flight. Thus, the power of QTC is now extended to the full dimensionality of physical space, enabling succinct yet rich representations of spatial interactions between agents.

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Section: Introductionmentioning

confidence: 99%

QTC3D: Extending the qualitative trajectory calculus to three dimensions

Mavridis

Bellotto

Iliopoulos

et al. 2015

Information Sciences

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“…In QTC, the interactions are considered to be the changes in the Euclidean distance between two MPOs. While insightful QTC has, until recently, remained largely conceptual, and new methods for inferring meaningful knowledge from qualitative spatio-temporal information remain sorely needed [22,23].…”

Section: Introductionmentioning

confidence: 99%

Movement Pattern Analysis Based on Sequence Signatures

Chavoshi

Baets

Neutens

et al. 2015

IJGI

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Increased affordability and deployment of advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery. Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis. This research focuses on the latter and uses the qualitative trajectory calculus (QTC), a type of calculus that represents qualitative data on moving point objects (MPOs), and establishes a framework to analyze the relative movement of multiple MPOs. A visualization technique called sequence signature (SESI) is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of relative movement patterns of multiple MPOs. The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer. The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains.

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“…As shown in [9], QTC B and QTC C can be "manually" combined to represent and reason about HRSIs. In the following section, however, we formalise and automatise this process.…”

Section: The Qualitative Trajectory Calculusmentioning

confidence: 99%

“…Hall's personal space [7]. Instead of using "manually" crafted transitions between the different QTC variants [9] we propose a probabilistic model with increasing granularity of the QTC representation depending on the distance of human and robot trained from real world data. This does not only give the possibility to model this crucial HRSI metric in QTC but also makes use of more detailed action representation only when robot and human are in close vicinity to one another.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, it is more important to represent qualitatively how the agents move with respect to each other, in order to understand underlying social rules and conventions. In our previous work, we proposed a qualitative framework based on the analysis of relative position and movement direction between two interacting agents on a 2D environment [8], [9], [10]. In particular, to reduce the space domain and focus only on those terms relevant to HRSI, we adopted the well-defined set of symbols and relations provided by the Qualitative Trajectory Calculus (QTC), a formalism representing the relative motion of two points in space in a qualitative framework [11].…”

Section: Introductionmentioning

confidence: 99%

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Social distance augmented qualitative trajectory calculus for Human-Robot Spatial Interaction

Dondrup

Bellotto

Hanheide

2014

The 23rd IEEE International Symposium on Robot and Human Interactive Communication

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Abstract-In this paper we propose to augment a wellestablished Qualitative Trajectory Calculus (QTC) by incorporating social distances into the model to facilitate a richer and more powerful representation of Human-Robot Spatial Interaction (HRSI). By combining two variants of QTC that implement different resolutions and switching between them based on distance thresholds we show that we are able to both reduce the complexity of the representation and at the same time enrich QTC with one of the core HRSI concepts: proxemics. Building on this novel integrated QTC model, we propose to represent the joint spatial behaviour of a human and a robot employing a probabilistic representation based on Hidden Markov Models. We show the appropriateness of our approach by encoding different HRSI behaviours observed in a human-robot interaction study and show how the models can be used to represent and classify these behaviours using social distance-augmented QTC.

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Qualitative Design and Implementation of Human-Robot Spatial Interactions

Cited by 17 publications

References 15 publications

QTC3D: Extending the qualitative trajectory calculus to three dimensions

QTC3D: Extending the qualitative trajectory calculus to three dimensions

Movement Pattern Analysis Based on Sequence Signatures

Social distance augmented qualitative trajectory calculus for Human-Robot Spatial Interaction

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